Getting the below error for a adaptive autosar model during build
Error:Unexpected or internal error encountered in "in CGIR: B:matlabsrccg_irbaseNamespace.cpp line 13: B:matlabsrccg_irbaseNamespace.cpp(13): In getOrCreateChild: Assertion failed: !aName.empty() Anonymous Namespaces are not supported
". Please report this to MathWorks if you can cause it to recurGetting the below error for a adaptive autosar model during build
Error:Unexpected or internal error encountered in "in CGIR: B:matlabsrccg_irbaseNamespace.cpp line 13: B:matlabsrccg_irbaseNamespace.cpp(13): In getOrCreateChild: Assertion failed: !aName.empty() Anonymous Namespaces are not supported
". Please report this to MathWorks if you can cause it to recur Getting the below error for a adaptive autosar model during build
Error:Unexpected or internal error encountered in "in CGIR: B:matlabsrccg_irbaseNamespace.cpp line 13: B:matlabsrccg_irbaseNamespace.cpp(13): In getOrCreateChild: Assertion failed: !aName.empty() Anonymous Namespaces are not supported
". Please report this to MathWorks if you can cause it to recur namespaces MATLAB Answers — New Questions

​

Perhaps, an FBX could be used to ‘cover’ a robot or a rigid body tree in the VIRTUAL WORLD and then be exported to the UNREAL ENGINE either as a SKELETAL MESH, FBX, or as a data flow of movements to the UNREAL ENGINE.Perhaps, an FBX could be used to ‘cover’ a robot or a rigid body tree in the VIRTUAL WORLD and then be exported to the UNREAL ENGINE either as a SKELETAL MESH, FBX, or as a data flow of movements to the UNREAL ENGINE. Perhaps, an FBX could be used to ‘cover’ a robot or a rigid body tree in the VIRTUAL WORLD and then be exported to the UNREAL ENGINE either as a SKELETAL MESH, FBX, or as a data flow of movements to the UNREAL ENGINE. fbx, unreal engine MATLAB Answers — New Questions

​

Hello Team,

I have a thermal model with conductive elements and have created a cylindrical cell model in Matlab 2021b, when I try to connect the cylindrical cells parallelly with current input and run the model for 10 sec it is taking 50 min of compliation time, 10 min of initilization time and 2 min of run time.
As the compilation time is too large, I converted the cell model to FMU and use the FMU inplace of open simscape mode and run the model for 10 sec and I observed that the compilation time is negligable, initilization time is around 10 min and the runtime is roughly about 70 min for 10sec of simulation time.

How to make this FMU model run with Realtime factor?
Please guide us with this.

Thanks in advanceHello Team,

I have a thermal model with conductive elements and have created a cylindrical cell model in Matlab 2021b, when I try to connect the cylindrical cells parallelly with current input and run the model for 10 sec it is taking 50 min of compliation time, 10 min of initilization time and 2 min of run time.
As the compilation time is too large, I converted the cell model to FMU and use the FMU inplace of open simscape mode and run the model for 10 sec and I observed that the compilation time is negligable, initilization time is around 10 min and the runtime is roughly about 70 min for 10sec of simulation time.

How to make this FMU model run with Realtime factor?
Please guide us with this.

Thanks in advance Hello Team,

I have a thermal model with conductive elements and have created a cylindrical cell model in Matlab 2021b, when I try to connect the cylindrical cells parallelly with current input and run the model for 10 sec it is taking 50 min of compliation time, 10 min of initilization time and 2 min of run time.
As the compilation time is too large, I converted the cell model to FMU and use the FMU inplace of open simscape mode and run the model for 10 sec and I observed that the compilation time is negligable, initilization time is around 10 min and the runtime is roughly about 70 min for 10sec of simulation time.

How to make this FMU model run with Realtime factor?
Please guide us with this.

Thanks in advance fmu, simscape, thermal, runtime, compilation, initilization MATLAB Answers — New Questions

​

Hello!
I am currently trying to understand how I could improve my model. Seen below is the connection:

Some values fed to the synchrnous motor and the outputs was seen as so:

Values above are calculated from the input. and the values below are from the motor.
Anyone have any ideas on how to improve the results?Hello!
I am currently trying to understand how I could improve my model. Seen below is the connection:

Some values fed to the synchrnous motor and the outputs was seen as so:

Values above are calculated from the input. and the values below are from the motor.
Anyone have any ideas on how to improve the results? Hello!
I am currently trying to understand how I could improve my model. Seen below is the connection:

Some values fed to the synchrnous motor and the outputs was seen as so:

Values above are calculated from the input. and the values below are from the motor.
Anyone have any ideas on how to improve the results? simulink, simscape, matlab, electric_motor_control MATLAB Answers — New Questions

​

I want to estimate the positions and orientations of two cameras, so I captured images of a checkerboard, created 27 pairs, and performed stereo calibration. The distance between the cameras is approximately 4.5 meters, and the checkerboard was photographed from various angles at distances ranging from 1 to 6 meters from the cameras. The overall average reprojection error during this process was 0.28 pixels.
The results of the stereo calibration are shown in the attached image. To make the issue more understandable, the image is displayed in the x-z plane. Below, I will list the ‘data from this image’ and ‘PoseCamera2’s T’ obtained from the stereo calibration.
Visual data: approximately [-2700, -500, 3500]…①
PoseCamera2’s T: [3540, -734, 2748]…②
When comparing the results of ① and ②, it seems that the x and z components are reversed. I would like to know why the results of ① and ②, which are supposed to be the same, do not match. Additionally, the actual positional relationship between Camera 1 and Camera 2 nearly matches ①, so I would like to understand the reason for this as well.

Regarding the cause of the discrepancy between ① and ②, I have considered the following points, but I have not resolved the issue:
Differences due to coordinate systems：I think the results’ coordinate systems in ① and ② might be different. However, since PoseCamera2 output by stereo calibration uses the optical center of Camera 1 as the origin, it seems that the origin of the visual data should match. Therefore, I believe that the coordinate systems of ① and ② are the same.
Misunderstanding in handling R and T：PoseCamera2 represents the relative pose that transforms Camera 2’s pose into Camera 1’s pose. If we represent the pose of Camera 1 as [R1, t1; 0 1], the pose of Camera 2 as [R2, t2; 0 1], and PoseCamera2 as [R, T; 0 1], the relationship [R1, t1; 0 1] = [R, T; 0 1] * [R2, t2; 0 1] holds, leading to: R1 = R * R2…③ t1 = R * t2 + T…④ I was previously informed by a STAFF member about this relationship. Here, even when considering only the position and ignoring the orientation of R, substituting ② into ⑤ does not align the pose of Camera 2 with Camera 1. Therefore, I suspect there might be a misunderstanding in my handling of R and T.
As a supplementary note, the values of R are [0.051, 0.085, -0.99; -0.31, 0.95, 0.065; 0.95, 0.31, 0.075].I want to estimate the positions and orientations of two cameras, so I captured images of a checkerboard, created 27 pairs, and performed stereo calibration. The distance between the cameras is approximately 4.5 meters, and the checkerboard was photographed from various angles at distances ranging from 1 to 6 meters from the cameras. The overall average reprojection error during this process was 0.28 pixels.
The results of the stereo calibration are shown in the attached image. To make the issue more understandable, the image is displayed in the x-z plane. Below, I will list the ‘data from this image’ and ‘PoseCamera2’s T’ obtained from the stereo calibration.
Visual data: approximately [-2700, -500, 3500]…①
PoseCamera2’s T: [3540, -734, 2748]…②
When comparing the results of ① and ②, it seems that the x and z components are reversed. I would like to know why the results of ① and ②, which are supposed to be the same, do not match. Additionally, the actual positional relationship between Camera 1 and Camera 2 nearly matches ①, so I would like to understand the reason for this as well.

Regarding the cause of the discrepancy between ① and ②, I have considered the following points, but I have not resolved the issue:
Differences due to coordinate systems：I think the results’ coordinate systems in ① and ② might be different. However, since PoseCamera2 output by stereo calibration uses the optical center of Camera 1 as the origin, it seems that the origin of the visual data should match. Therefore, I believe that the coordinate systems of ① and ② are the same.
Misunderstanding in handling R and T：PoseCamera2 represents the relative pose that transforms Camera 2’s pose into Camera 1’s pose. If we represent the pose of Camera 1 as [R1, t1; 0 1], the pose of Camera 2 as [R2, t2; 0 1], and PoseCamera2 as [R, T; 0 1], the relationship [R1, t1; 0 1] = [R, T; 0 1] * [R2, t2; 0 1] holds, leading to: R1 = R * R2…③ t1 = R * t2 + T…④ I was previously informed by a STAFF member about this relationship. Here, even when considering only the position and ignoring the orientation of R, substituting ② into ⑤ does not align the pose of Camera 2 with Camera 1. Therefore, I suspect there might be a misunderstanding in my handling of R and T.
As a supplementary note, the values of R are [0.051, 0.085, -0.99; -0.31, 0.95, 0.065; 0.95, 0.31, 0.075]. I want to estimate the positions and orientations of two cameras, so I captured images of a checkerboard, created 27 pairs, and performed stereo calibration. The distance between the cameras is approximately 4.5 meters, and the checkerboard was photographed from various angles at distances ranging from 1 to 6 meters from the cameras. The overall average reprojection error during this process was 0.28 pixels.
The results of the stereo calibration are shown in the attached image. To make the issue more understandable, the image is displayed in the x-z plane. Below, I will list the ‘data from this image’ and ‘PoseCamera2’s T’ obtained from the stereo calibration.
Visual data: approximately [-2700, -500, 3500]…①
PoseCamera2’s T: [3540, -734, 2748]…②
When comparing the results of ① and ②, it seems that the x and z components are reversed. I would like to know why the results of ① and ②, which are supposed to be the same, do not match. Additionally, the actual positional relationship between Camera 1 and Camera 2 nearly matches ①, so I would like to understand the reason for this as well.

Regarding the cause of the discrepancy between ① and ②, I have considered the following points, but I have not resolved the issue:
Differences due to coordinate systems：I think the results’ coordinate systems in ① and ② might be different. However, since PoseCamera2 output by stereo calibration uses the optical center of Camera 1 as the origin, it seems that the origin of the visual data should match. Therefore, I believe that the coordinate systems of ① and ② are the same.
Misunderstanding in handling R and T：PoseCamera2 represents the relative pose that transforms Camera 2’s pose into Camera 1’s pose. If we represent the pose of Camera 1 as [R1, t1; 0 1], the pose of Camera 2 as [R2, t2; 0 1], and PoseCamera2 as [R, T; 0 1], the relationship [R1, t1; 0 1] = [R, T; 0 1] * [R2, t2; 0 1] holds, leading to: R1 = R * R2…③ t1 = R * t2 + T…④ I was previously informed by a STAFF member about this relationship. Here, even when considering only the position and ignoring the orientation of R, substituting ② into ⑤ does not align the pose of Camera 2 with Camera 1. Therefore, I suspect there might be a misunderstanding in my handling of R and T.
As a supplementary note, the values of R are [0.051, 0.085, -0.99; -0.31, 0.95, 0.065; 0.95, 0.31, 0.075]. stereocalibration, stereoparameters MATLAB Answers — New Questions

​

Having some trouble with this assignment.

Write a function called minimax that takes M, a matrix input argument and returns mmr, a row vector containing the absolute values of the difference between the maximum and minimum valued elements in each row. As a second output argument called mmm, it provides the difference between the maximum and minimum element in the entire matrix. See the code below for an example:
>> A = randi(100,3,4)
A =
66 94 75 18
4 68 40 71
85 76 66 4
>> [x, y] = minimax(A)
x =
76 67 81
y =
90
%Code to call your function
[mmr, mmm] = minimax([1:4;5:8;9:12])Having some trouble with this assignment.

Write a function called minimax that takes M, a matrix input argument and returns mmr, a row vector containing the absolute values of the difference between the maximum and minimum valued elements in each row. As a second output argument called mmm, it provides the difference between the maximum and minimum element in the entire matrix. See the code below for an example:
>> A = randi(100,3,4)
A =
66 94 75 18
4 68 40 71
85 76 66 4
>> [x, y] = minimax(A)
x =
76 67 81
y =
90
%Code to call your function
[mmr, mmm] = minimax([1:4;5:8;9:12]) Having some trouble with this assignment.

Write a function called minimax that takes M, a matrix input argument and returns mmr, a row vector containing the absolute values of the difference between the maximum and minimum valued elements in each row. As a second output argument called mmm, it provides the difference between the maximum and minimum element in the entire matrix. See the code below for an example:
>> A = randi(100,3,4)
A =
66 94 75 18
4 68 40 71
85 76 66 4
>> [x, y] = minimax(A)
x =
76 67 81
y =
90
%Code to call your function
[mmr, mmm] = minimax([1:4;5:8;9:12]) coursera, functions MATLAB Answers — New Questions

​

This is in relation to the move from LayerGraphs, trainNetwork, and resnetLayers to dlnetworks, trainnet, and resnetNetwork.
I have a dataset consisting of 125×125 images, with 8 pixel channels instead of the usual 3 for RGB. With the older resnetLayers (which creates a ResNet LayerGraph) and trainNetwork, I was able to store this data as cells in a table and train with that. However, resnetLayers and trainNetwork are no longer recommended by MATLAB, and they recommend using resnetNetwork (which creates a ResNet dlnetwork) and trainnet instead. I want to keep up with the more modern and supported implementations, so I tried rewriting my code to use these, but I run into a problem where it seems trainnet won’t accept this format of data anymore, and I haven’t yet found a way to make it work. How should I go about passing this data to trainnet?

%Load the training data
load("dataset.mat", "traindata");
traindata
%Train a ResNet LayerGraph using the old functions
imageSize = [125 125 8];
numClasses = 2;
layers = resnetLayers(imageSize,numClasses);
opts = trainingOptions("adam",…
"ExecutionEnvironment","cpu",…
"InitialLearnRate",0.0001,…
"MaxEpochs",1);
trainedNetwork = trainNetwork(traindata,layers,opts)
%Try to train a ResNet dlnetwork with the new functions, get an error
dlresnet = resnetNetwork(imageSize,numClasses);
dlresnet = initialize(dlresnet);
trainedDlnetwork = trainnet(traindata,dlresnet,"crossentropy",opts)This is in relation to the move from LayerGraphs, trainNetwork, and resnetLayers to dlnetworks, trainnet, and resnetNetwork.
I have a dataset consisting of 125×125 images, with 8 pixel channels instead of the usual 3 for RGB. With the older resnetLayers (which creates a ResNet LayerGraph) and trainNetwork, I was able to store this data as cells in a table and train with that. However, resnetLayers and trainNetwork are no longer recommended by MATLAB, and they recommend using resnetNetwork (which creates a ResNet dlnetwork) and trainnet instead. I want to keep up with the more modern and supported implementations, so I tried rewriting my code to use these, but I run into a problem where it seems trainnet won’t accept this format of data anymore, and I haven’t yet found a way to make it work. How should I go about passing this data to trainnet?

%Load the training data
load("dataset.mat", "traindata");
traindata
%Train a ResNet LayerGraph using the old functions
imageSize = [125 125 8];
numClasses = 2;
layers = resnetLayers(imageSize,numClasses);
opts = trainingOptions("adam",…
"ExecutionEnvironment","cpu",…
"InitialLearnRate",0.0001,…
"MaxEpochs",1);
trainedNetwork = trainNetwork(traindata,layers,opts)
%Try to train a ResNet dlnetwork with the new functions, get an error
dlresnet = resnetNetwork(imageSize,numClasses);
dlresnet = initialize(dlresnet);
trainedDlnetwork = trainnet(traindata,dlresnet,"crossentropy",opts) This is in relation to the move from LayerGraphs, trainNetwork, and resnetLayers to dlnetworks, trainnet, and resnetNetwork.
I have a dataset consisting of 125×125 images, with 8 pixel channels instead of the usual 3 for RGB. With the older resnetLayers (which creates a ResNet LayerGraph) and trainNetwork, I was able to store this data as cells in a table and train with that. However, resnetLayers and trainNetwork are no longer recommended by MATLAB, and they recommend using resnetNetwork (which creates a ResNet dlnetwork) and trainnet instead. I want to keep up with the more modern and supported implementations, so I tried rewriting my code to use these, but I run into a problem where it seems trainnet won’t accept this format of data anymore, and I haven’t yet found a way to make it work. How should I go about passing this data to trainnet?

%Load the training data
load("dataset.mat", "traindata");
traindata
%Train a ResNet LayerGraph using the old functions
imageSize = [125 125 8];
numClasses = 2;
layers = resnetLayers(imageSize,numClasses);
opts = trainingOptions("adam",…
"ExecutionEnvironment","cpu",…
"InitialLearnRate",0.0001,…
"MaxEpochs",1);
trainedNetwork = trainNetwork(traindata,layers,opts)
%Try to train a ResNet dlnetwork with the new functions, get an error
dlresnet = resnetNetwork(imageSize,numClasses);
dlresnet = initialize(dlresnet);
trainedDlnetwork = trainnet(traindata,dlresnet,"crossentropy",opts) machine learning, resnet, computer vision MATLAB Answers — New Questions

​

I am trying to make an xray image out of given x, y, z coordinates. Here is my code below:

fileID = fopen(‘Chest_Xray_Raw_Data.txt’, ‘r’);
data = textscan(fileID, ‘%f,%f,%f,%f’, ‘Delimiter’, ‘,’);
fclose(fileID);
% Extract x, y, z coordinates and grayscale values
x = data{1};
y = data{2};
z = data{3}; % If needed, otherwise ignore
grayscale = data{4};
% Determine the size of the image
maxX = int64(max(x));
maxY = int64(max(y));
% Normalize coordinates to fit into the pixel grid
x = round(x – min(x) + 1);
y = round(y – min(y) + 1);
% Initialize the image matrix
imageMatrix = zeros(maxY, maxX);
% Populate the image matrix with grayscale values
for i = 1:length(x)
imageMatrix(y(i), x(i)) = grayscale(i);
end
% Display the image
figure;
imshow(imageMatrix, []);
title(‘Reconstructed Image from Raw Data’);
colormap(gray); % Use grayscale colormap
colorbar;

An example of the data I am given is this, but obviously larger:
+4.23789300E+002, +0.00000000E+000, +0.00000000E+000, +420
+4.23619400E+002, +0.00000000E+000, +0.00000000E+000, +420
+4.23449400E+002, +0.00000000E+000, +0.00000000E+000, +420
+4.23279500E+002, +0.00000000E+000, +0.00000000E+000, +420

When I run it, I get this message
"Index exceeds the number of array elements. Index must not exceed 0.

Error in untitled (line 24)
imageMatrix(y(i), x(i)) = grayscale(i);"

How can I get rid of this error message? Thanks!I am trying to make an xray image out of given x, y, z coordinates. Here is my code below:

fileID = fopen(‘Chest_Xray_Raw_Data.txt’, ‘r’);
data = textscan(fileID, ‘%f,%f,%f,%f’, ‘Delimiter’, ‘,’);
fclose(fileID);
% Extract x, y, z coordinates and grayscale values
x = data{1};
y = data{2};
z = data{3}; % If needed, otherwise ignore
grayscale = data{4};
% Determine the size of the image
maxX = int64(max(x));
maxY = int64(max(y));
% Normalize coordinates to fit into the pixel grid
x = round(x – min(x) + 1);
y = round(y – min(y) + 1);
% Initialize the image matrix
imageMatrix = zeros(maxY, maxX);
% Populate the image matrix with grayscale values
for i = 1:length(x)
imageMatrix(y(i), x(i)) = grayscale(i);
end
% Display the image
figure;
imshow(imageMatrix, []);
title(‘Reconstructed Image from Raw Data’);
colormap(gray); % Use grayscale colormap
colorbar;

An example of the data I am given is this, but obviously larger:
+4.23789300E+002, +0.00000000E+000, +0.00000000E+000, +420
+4.23619400E+002, +0.00000000E+000, +0.00000000E+000, +420
+4.23449400E+002, +0.00000000E+000, +0.00000000E+000, +420
+4.23279500E+002, +0.00000000E+000, +0.00000000E+000, +420

When I run it, I get this message
"Index exceeds the number of array elements. Index must not exceed 0.

Error in untitled (line 24)
imageMatrix(y(i), x(i)) = grayscale(i);"

How can I get rid of this error message? Thanks! I am trying to make an xray image out of given x, y, z coordinates. Here is my code below:

fileID = fopen(‘Chest_Xray_Raw_Data.txt’, ‘r’);
data = textscan(fileID, ‘%f,%f,%f,%f’, ‘Delimiter’, ‘,’);
fclose(fileID);
% Extract x, y, z coordinates and grayscale values
x = data{1};
y = data{2};
z = data{3}; % If needed, otherwise ignore
grayscale = data{4};
% Determine the size of the image
maxX = int64(max(x));
maxY = int64(max(y));
% Normalize coordinates to fit into the pixel grid
x = round(x – min(x) + 1);
y = round(y – min(y) + 1);
% Initialize the image matrix
imageMatrix = zeros(maxY, maxX);
% Populate the image matrix with grayscale values
for i = 1:length(x)
imageMatrix(y(i), x(i)) = grayscale(i);
end
% Display the image
figure;
imshow(imageMatrix, []);
title(‘Reconstructed Image from Raw Data’);
colormap(gray); % Use grayscale colormap
colorbar;

An example of the data I am given is this, but obviously larger:
+4.23789300E+002, +0.00000000E+000, +0.00000000E+000, +420
+4.23619400E+002, +0.00000000E+000, +0.00000000E+000, +420
+4.23449400E+002, +0.00000000E+000, +0.00000000E+000, +420
+4.23279500E+002, +0.00000000E+000, +0.00000000E+000, +420

When I run it, I get this message
"Index exceeds the number of array elements. Index must not exceed 0.

Error in untitled (line 24)
imageMatrix(y(i), x(i)) = grayscale(i);"

How can I get rid of this error message? Thanks! error, grayscale MATLAB Answers — New Questions

​

Hello,
I am trying to analyze some doppler shifts on a spectrogram. I am using the Matlab Curve Fitter Tool to fit a curve to very specific data. The curve fitter works well. It generates polynomial parameters but when I try to graph this polynomial in a normal script, the output looks nothing like the graph in the curve fitter.

Here is the curve fitter:

Here is the curve fitter polynomial output:

And when I try taking these values (p1, … p10) and plotting the polynomial in a regular script, the output looks like this:

Which looks nothing like the curve in the curve fitter app. Additionally, the y-axis for the script graph is way off. I have tried playing around with the scaling outputs that the polyfit() function gives me but I haven’t made any progress. I have also tried to use the "center and scale" option but haven’t gotten that to work either. I clearly don’t understand something fundamental with this tool.
Thanks in advance for any help!
Here is my script’s code: (p values pulled straight from the curve fitter app)
p1 = 0.0067;
p2 = -1.7909;
p3 = 155.6940;
p4 = 1.1965e+03;
p5 = -1.2672e+06;
p6 = 1.1048e+08;
p7 = -4.9186e+09;
p8 = 1.258e+11;
p9 = -1.7629e+12;
p10 = 1.0551e+13;

x = 40:0.01:50;
p = [p1 p2 p3 p4 p5 p6 p7 p8 p9 p10];
plot(x, polyval(p, x));Hello,
I am trying to analyze some doppler shifts on a spectrogram. I am using the Matlab Curve Fitter Tool to fit a curve to very specific data. The curve fitter works well. It generates polynomial parameters but when I try to graph this polynomial in a normal script, the output looks nothing like the graph in the curve fitter.

Here is the curve fitter:

Here is the curve fitter polynomial output:

And when I try taking these values (p1, … p10) and plotting the polynomial in a regular script, the output looks like this:

Which looks nothing like the curve in the curve fitter app. Additionally, the y-axis for the script graph is way off. I have tried playing around with the scaling outputs that the polyfit() function gives me but I haven’t made any progress. I have also tried to use the "center and scale" option but haven’t gotten that to work either. I clearly don’t understand something fundamental with this tool.
Thanks in advance for any help!
Here is my script’s code: (p values pulled straight from the curve fitter app)
p1 = 0.0067;
p2 = -1.7909;
p3 = 155.6940;
p4 = 1.1965e+03;
p5 = -1.2672e+06;
p6 = 1.1048e+08;
p7 = -4.9186e+09;
p8 = 1.258e+11;
p9 = -1.7629e+12;
p10 = 1.0551e+13;

x = 40:0.01:50;
p = [p1 p2 p3 p4 p5 p6 p7 p8 p9 p10];
plot(x, polyval(p, x)); Hello,
I am trying to analyze some doppler shifts on a spectrogram. I am using the Matlab Curve Fitter Tool to fit a curve to very specific data. The curve fitter works well. It generates polynomial parameters but when I try to graph this polynomial in a normal script, the output looks nothing like the graph in the curve fitter.

Here is the curve fitter:

Here is the curve fitter polynomial output:

And when I try taking these values (p1, … p10) and plotting the polynomial in a regular script, the output looks like this:

Which looks nothing like the curve in the curve fitter app. Additionally, the y-axis for the script graph is way off. I have tried playing around with the scaling outputs that the polyfit() function gives me but I haven’t made any progress. I have also tried to use the "center and scale" option but haven’t gotten that to work either. I clearly don’t understand something fundamental with this tool.
Thanks in advance for any help!
Here is my script’s code: (p values pulled straight from the curve fitter app)
p1 = 0.0067;
p2 = -1.7909;
p3 = 155.6940;
p4 = 1.1965e+03;
p5 = -1.2672e+06;
p6 = 1.1048e+08;
p7 = -4.9186e+09;
p8 = 1.258e+11;
p9 = -1.7629e+12;
p10 = 1.0551e+13;

x = 40:0.01:50;
p = [p1 p2 p3 p4 p5 p6 p7 p8 p9 p10];
plot(x, polyval(p, x)); curve fitter, line of best fit, polynomial, matlab, doppler, doppler shift, spectrogram, curve fitting MATLAB Answers — New Questions

​

Hello, I wanted to create a MEX file in MATLAB, but I couldn’t do that because of the following message in the "build log":
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "BPmimo2C_data.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
BPmimo2C_data.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "BPmimo2C_initialize.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
BPmimo2C_initialize.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "BPmimo2C_terminate.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
BPmimo2C_terminate.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "BPmimo2C.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
BPmimo2C.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "interface/_coder_BPmimo2C_info.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
_coder_BPmimo2C_info.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "interface/_coder_BPmimo2C_api.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
_coder_BPmimo2C_api.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "interface/_coder_BPmimo2C_mex.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
_coder_BPmimo2C_mex.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "MWCudaDimUtility.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
MWCudaDimUtility.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "cpp_mexapi_version.cpp"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
cpp_mexapi_version.cpp
nvcc -m64 -Wl,–no-undefined -shared -static -L"C:Program FilesMATLABR2018bexternlibwin64mingw64" -llibmx -llibmex -llibmat -lm -llibmwlapack -llibmwblas -llibMatlabDataArray -llibMatlabEngine -Xnvlink -w -Wno-deprecated-gpu-targets -Xlinker /NODEFAULTLIB:libcmt.lib -o BPmimo2C_mex.mexw64 -arch sm_35 BPmimo2C_data.obj BPmimo2C_initialize.obj BPmimo2C_terminate.obj BPmimo2C.obj _coder_BPmimo2C_info.obj _coder_BPmimo2C_api.obj _coder_BPmimo2C_mex.obj MWCudaDimUtility.obj cpp_mexapi_version.obj -L"C:Program FilesNVIDIA GPU Computing ToolkitCUDAv11.2libx64" cuda.lib cudart.lib cublas.lib cusolver.lib cufft.lib -Xlinker libemlrt.lib,libcovrt.lib,libut.lib,libmwmathutil.lib,/export:mexFunction,/export:emlrtMexFcnProperties 
nvcc fatal : Unknown option ‘-Wl,–no-undefined’
gmake: *** [BPmimo2C_mex.mexw64] Error 1

Warning: Selected MEX compiler ‘MinGW64 Compiler (C++)’ is not supported for GPU code generation. Refer to the GPU Coder documentation for a list of supported GPU MEX compilers. 
> In coder.gpu.getDefaultGpuToolchain
  In emlckernel
  In emlckernel
  In emlcprivate
  In coder.internal.gui.codegenWrapper
  In codeUnifiedProject
  In codeUnifiedProject
  In emlcprivate 
??? Build error: C++ compiler produced errors. See the Build Log for further details.

Code generation failed: View Error Report
I have previously installed visual studio 2019, and added the "cl.exe" path to my environmental variable. Moreover, Microsoft visual C++ redistributable x64 2015-2019 is currently available on my system.
Here is the added path:

What do you think about where my problem come from?
Any help would be appreciated.
Thank youHello, I wanted to create a MEX file in MATLAB, but I couldn’t do that because of the following message in the "build log":
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "BPmimo2C_data.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
BPmimo2C_data.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "BPmimo2C_initialize.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
BPmimo2C_initialize.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "BPmimo2C_terminate.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
BPmimo2C_terminate.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "BPmimo2C.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
BPmimo2C.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "interface/_coder_BPmimo2C_info.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
_coder_BPmimo2C_info.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "interface/_coder_BPmimo2C_api.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
_coder_BPmimo2C_api.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "interface/_coder_BPmimo2C_mex.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
_coder_BPmimo2C_mex.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "MWCudaDimUtility.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
MWCudaDimUtility.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "cpp_mexapi_version.cpp"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
cpp_mexapi_version.cpp
nvcc -m64 -Wl,–no-undefined -shared -static -L"C:Program FilesMATLABR2018bexternlibwin64mingw64" -llibmx -llibmex -llibmat -lm -llibmwlapack -llibmwblas -llibMatlabDataArray -llibMatlabEngine -Xnvlink -w -Wno-deprecated-gpu-targets -Xlinker /NODEFAULTLIB:libcmt.lib -o BPmimo2C_mex.mexw64 -arch sm_35 BPmimo2C_data.obj BPmimo2C_initialize.obj BPmimo2C_terminate.obj BPmimo2C.obj _coder_BPmimo2C_info.obj _coder_BPmimo2C_api.obj _coder_BPmimo2C_mex.obj MWCudaDimUtility.obj cpp_mexapi_version.obj -L"C:Program FilesNVIDIA GPU Computing ToolkitCUDAv11.2libx64" cuda.lib cudart.lib cublas.lib cusolver.lib cufft.lib -Xlinker libemlrt.lib,libcovrt.lib,libut.lib,libmwmathutil.lib,/export:mexFunction,/export:emlrtMexFcnProperties 
nvcc fatal : Unknown option ‘-Wl,–no-undefined’
gmake: *** [BPmimo2C_mex.mexw64] Error 1

Warning: Selected MEX compiler ‘MinGW64 Compiler (C++)’ is not supported for GPU code generation. Refer to the GPU Coder documentation for a list of supported GPU MEX compilers. 
> In coder.gpu.getDefaultGpuToolchain
  In emlckernel
  In emlckernel
  In emlcprivate
  In coder.internal.gui.codegenWrapper
  In codeUnifiedProject
  In codeUnifiedProject
  In emlcprivate 
??? Build error: C++ compiler produced errors. See the Build Log for further details.

Code generation failed: View Error Report
I have previously installed visual studio 2019, and added the "cl.exe" path to my environmental variable. Moreover, Microsoft visual C++ redistributable x64 2015-2019 is currently available on my system.
Here is the added path:

What do you think about where my problem come from?
Any help would be appreciated.
Thank you Hello, I wanted to create a MEX file in MATLAB, but I couldn’t do that because of the following message in the "build log":
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "BPmimo2C_data.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
BPmimo2C_data.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "BPmimo2C_initialize.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
BPmimo2C_initialize.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "BPmimo2C_terminate.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
BPmimo2C_terminate.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "BPmimo2C.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
BPmimo2C.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "interface/_coder_BPmimo2C_info.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
_coder_BPmimo2C_info.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "interface/_coder_BPmimo2C_api.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
_coder_BPmimo2C_api.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "interface/_coder_BPmimo2C_mex.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
_coder_BPmimo2C_mex.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "MWCudaDimUtility.cu"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
MWCudaDimUtility.cu
nvcc -c -rdc=true -Xcompiler "/wd 4819" -Xcompiler "/MD" -Xcudafe "–diag_suppress=unsigned_compare_with_zero –diag_suppress=useless_type_qualifier_on_return_type" -D_GNU_SOURCE -DMATLAB_MEX_FILE -Wno-deprecated-declarations     -arch sm_35 -I "C:PROGRA~1MATLABR2018bsimulinkinclude" -I "C:PROGRA~1MATLABR2018btoolboxsharedsimtargets" -I "D:fekomultiple ring arraycodegenmexBPmimo2C" -I "D:fekomultiple ring array" -I ".interface" -I "C:PROGRA~1MATLABR2018bexterninclude" -I "." "cpp_mexapi_version.cpp"
nvcc warning : The ‘compute_35’, ‘compute_37’, ‘compute_50’, ‘sm_35’, ‘sm_37’ and ‘sm_50’ architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
cpp_mexapi_version.cpp
nvcc -m64 -Wl,–no-undefined -shared -static -L"C:Program FilesMATLABR2018bexternlibwin64mingw64" -llibmx -llibmex -llibmat -lm -llibmwlapack -llibmwblas -llibMatlabDataArray -llibMatlabEngine -Xnvlink -w -Wno-deprecated-gpu-targets -Xlinker /NODEFAULTLIB:libcmt.lib -o BPmimo2C_mex.mexw64 -arch sm_35 BPmimo2C_data.obj BPmimo2C_initialize.obj BPmimo2C_terminate.obj BPmimo2C.obj _coder_BPmimo2C_info.obj _coder_BPmimo2C_api.obj _coder_BPmimo2C_mex.obj MWCudaDimUtility.obj cpp_mexapi_version.obj -L"C:Program FilesNVIDIA GPU Computing ToolkitCUDAv11.2libx64" cuda.lib cudart.lib cublas.lib cusolver.lib cufft.lib -Xlinker libemlrt.lib,libcovrt.lib,libut.lib,libmwmathutil.lib,/export:mexFunction,/export:emlrtMexFcnProperties 
nvcc fatal : Unknown option ‘-Wl,–no-undefined’
gmake: *** [BPmimo2C_mex.mexw64] Error 1

Warning: Selected MEX compiler ‘MinGW64 Compiler (C++)’ is not supported for GPU code generation. Refer to the GPU Coder documentation for a list of supported GPU MEX compilers. 
> In coder.gpu.getDefaultGpuToolchain
  In emlckernel
  In emlckernel
  In emlcprivate
  In coder.internal.gui.codegenWrapper
  In codeUnifiedProject
  In codeUnifiedProject
  In emlcprivate 
??? Build error: C++ compiler produced errors. See the Build Log for further details.

Code generation failed: View Error Report
I have previously installed visual studio 2019, and added the "cl.exe" path to my environmental variable. Moreover, Microsoft visual C++ redistributable x64 2015-2019 is currently available on my system.
Here is the added path:

What do you think about where my problem come from?
Any help would be appreciated.
Thank you mex compiler, mex, gpu coder, matlab MATLAB Answers — New Questions

​