I need to take output from a "PCQI: A Patch-Structure Representation Method for Quality Assessment of Contrast Changed Images" code. But whenever i run this, it doesnt show anything at all. Not even an error. How can i solve this?

Demo.m
clc;
clear;

im1=imread(‘ref.png’);
im2=imread(‘contrast_changed.png’);
im1=double(rgb2gray(im1));
im2=double(rgb2gray(im2));
[mpcqi, pcqi_map] = PCQI(im1, im2);
PCQI.m (default value for window = fspecial(‘gaussian’, 11, 1.5); L = 256)
function [mpcqi, pcqi_map]= PCQI(img1, img2, window, L)
if (nargin < 2 || nargin > 4)
mpcqi = -Inf;
pcqi_map = -Inf;
return;
end

if (size(img1) ~= size(img2))
mpcqi = -Inf;
pcqi_map = -Inf;
return;
end

[M N] = size(img1);

if (nargin == 2)
if ((M < 11) || (N < 11))
mpcqi = -Inf;
pcqi_map = -Inf;
return
end
window = fspecial(‘gaussian’, 11, 1.5);
L = 256;
end

if (nargin == 3)
[H W] = size(window);
if ((H*W) < 4 || (H > M) || (W > N))
mpcqi = -Inf;
pcqi_map = -Inf;
return
end
L = 255;
end

if (nargin == 4)
[H W] = size(window);
if ((H*W) < 4 || (H > M) || (W > N))
mpcqi = -Inf;
pcqi_map = -Inf;
return
end
end

window = window/sum(sum(window));

mu1 = filter2(window, img1, ‘valid’);
mu2 = filter2(window, img2, ‘valid’);
mu1_sq = mu1.*mu1;
mu2_sq = mu2.*mu2;
mu1_mu2 = mu1.*mu2;
sigma1_sq = filter2(window, img1.*img1, ‘valid’) – mu1_sq;
sigma2_sq = filter2(window, img2.*img2, ‘valid’) – mu2_sq;
sigma12 = filter2(window, img1.*img2, ‘valid’) – mu1_mu2;

sigma1_sq = max(0, sigma1_sq);
sigma2_sq = max(0, sigma2_sq);

C=3;

pcqi_map = (4/pi) *atan((sigma12 + C )./(sigma1_sq + C ));
pcqi_map = pcqi_map .*((sigma12 + C) ./(sqrt(sigma1_sq).*sqrt(sigma2_sq) + C));
pcqi_map = pcqi_map .*exp(-abs(mu1-mu2)/L);

mpcqi = mean2(pcqi_map);

returnI need to take output from a "PCQI: A Patch-Structure Representation Method for Quality Assessment of Contrast Changed Images" code. But whenever i run this, it doesnt show anything at all. Not even an error. How can i solve this?

Demo.m
clc;
clear;

im1=imread(‘ref.png’);
im2=imread(‘contrast_changed.png’);
im1=double(rgb2gray(im1));
im2=double(rgb2gray(im2));
[mpcqi, pcqi_map] = PCQI(im1, im2);
PCQI.m (default value for window = fspecial(‘gaussian’, 11, 1.5); L = 256)
function [mpcqi, pcqi_map]= PCQI(img1, img2, window, L)
if (nargin < 2 || nargin > 4)
mpcqi = -Inf;
pcqi_map = -Inf;
return;
end

if (size(img1) ~= size(img2))
mpcqi = -Inf;
pcqi_map = -Inf;
return;
end

[M N] = size(img1);

if (nargin == 2)
if ((M < 11) || (N < 11))
mpcqi = -Inf;
pcqi_map = -Inf;
return
end
window = fspecial(‘gaussian’, 11, 1.5);
L = 256;
end

if (nargin == 3)
[H W] = size(window);
if ((H*W) < 4 || (H > M) || (W > N))
mpcqi = -Inf;
pcqi_map = -Inf;
return
end
L = 255;
end

if (nargin == 4)
[H W] = size(window);
if ((H*W) < 4 || (H > M) || (W > N))
mpcqi = -Inf;
pcqi_map = -Inf;
return
end
end

window = window/sum(sum(window));

mu1 = filter2(window, img1, ‘valid’);
mu2 = filter2(window, img2, ‘valid’);
mu1_sq = mu1.*mu1;
mu2_sq = mu2.*mu2;
mu1_mu2 = mu1.*mu2;
sigma1_sq = filter2(window, img1.*img1, ‘valid’) – mu1_sq;
sigma2_sq = filter2(window, img2.*img2, ‘valid’) – mu2_sq;
sigma12 = filter2(window, img1.*img2, ‘valid’) – mu1_mu2;

sigma1_sq = max(0, sigma1_sq);
sigma2_sq = max(0, sigma2_sq);

C=3;

pcqi_map = (4/pi) *atan((sigma12 + C )./(sigma1_sq + C ));
pcqi_map = pcqi_map .*((sigma12 + C) ./(sqrt(sigma1_sq).*sqrt(sigma2_sq) + C));
pcqi_map = pcqi_map .*exp(-abs(mu1-mu2)/L);

mpcqi = mean2(pcqi_map);

return I need to take output from a "PCQI: A Patch-Structure Representation Method for Quality Assessment of Contrast Changed Images" code. But whenever i run this, it doesnt show anything at all. Not even an error. How can i solve this?

Demo.m
clc;
clear;

im1=imread(‘ref.png’);
im2=imread(‘contrast_changed.png’);
im1=double(rgb2gray(im1));
im2=double(rgb2gray(im2));
[mpcqi, pcqi_map] = PCQI(im1, im2);
PCQI.m (default value for window = fspecial(‘gaussian’, 11, 1.5); L = 256)
function [mpcqi, pcqi_map]= PCQI(img1, img2, window, L)
if (nargin < 2 || nargin > 4)
mpcqi = -Inf;
pcqi_map = -Inf;
return;
end

if (size(img1) ~= size(img2))
mpcqi = -Inf;
pcqi_map = -Inf;
return;
end

[M N] = size(img1);

if (nargin == 2)
if ((M < 11) || (N < 11))
mpcqi = -Inf;
pcqi_map = -Inf;
return
end
window = fspecial(‘gaussian’, 11, 1.5);
L = 256;
end

if (nargin == 3)
[H W] = size(window);
if ((H*W) < 4 || (H > M) || (W > N))
mpcqi = -Inf;
pcqi_map = -Inf;
return
end
L = 255;
end

if (nargin == 4)
[H W] = size(window);
if ((H*W) < 4 || (H > M) || (W > N))
mpcqi = -Inf;
pcqi_map = -Inf;
return
end
end

window = window/sum(sum(window));

mu1 = filter2(window, img1, ‘valid’);
mu2 = filter2(window, img2, ‘valid’);
mu1_sq = mu1.*mu1;
mu2_sq = mu2.*mu2;
mu1_mu2 = mu1.*mu2;
sigma1_sq = filter2(window, img1.*img1, ‘valid’) – mu1_sq;
sigma2_sq = filter2(window, img2.*img2, ‘valid’) – mu2_sq;
sigma12 = filter2(window, img1.*img2, ‘valid’) – mu1_mu2;

sigma1_sq = max(0, sigma1_sq);
sigma2_sq = max(0, sigma2_sq);

C=3;

pcqi_map = (4/pi) *atan((sigma12 + C )./(sigma1_sq + C ));
pcqi_map = pcqi_map .*((sigma12 + C) ./(sqrt(sigma1_sq).*sqrt(sigma2_sq) + C));
pcqi_map = pcqi_map .*exp(-abs(mu1-mu2)/L);

mpcqi = mean2(pcqi_map);

return image analysis, pcqi MATLAB Answers — New Questions

​

Hi I am porting a script I had in Python to Matlab. Also returning to MATLAB after a decade, so pardon me if it’s too basic.

The key issue I am having is, retrieving premapped items from a cell array. Example, I have:

label_names={"assds", "Sasas", "Asasa", "assds"}
indices={[1 3 2]} %note that this can have varying lengths from 1 to full length of the label array.
label_names(indices) %of course returns an error

Error is "Unable to use a value of type cell as an index."
What is the best way to achieve this – retreive items based on a cell array of indices – as cleanly as possible?

PS: The reason they are cell arrays has to do with varying lengths. To avoid X-Y problem, lets assume rest of the code is done optimally.

Thanks!Hi I am porting a script I had in Python to Matlab. Also returning to MATLAB after a decade, so pardon me if it’s too basic.

The key issue I am having is, retrieving premapped items from a cell array. Example, I have:

label_names={"assds", "Sasas", "Asasa", "assds"}
indices={[1 3 2]} %note that this can have varying lengths from 1 to full length of the label array.
label_names(indices) %of course returns an error

Error is "Unable to use a value of type cell as an index."
What is the best way to achieve this – retreive items based on a cell array of indices – as cleanly as possible?

PS: The reason they are cell arrays has to do with varying lengths. To avoid X-Y problem, lets assume rest of the code is done optimally.

Thanks! Hi I am porting a script I had in Python to Matlab. Also returning to MATLAB after a decade, so pardon me if it’s too basic.

The key issue I am having is, retrieving premapped items from a cell array. Example, I have:

label_names={"assds", "Sasas", "Asasa", "assds"}
indices={[1 3 2]} %note that this can have varying lengths from 1 to full length of the label array.
label_names(indices) %of course returns an error

Error is "Unable to use a value of type cell as an index."
What is the best way to achieve this – retreive items based on a cell array of indices – as cleanly as possible?

PS: The reason they are cell arrays has to do with varying lengths. To avoid X-Y problem, lets assume rest of the code is done optimally.

Thanks! cell array, indexing MATLAB Answers — New Questions

​

This is not circle finding in an image, which has been well covered, but in an array.
I have an array P with several approximately-circular areas of a low value. I would like to find the centres of those areas to calibrate my device. Here is a contour 2D plot of P. The contour plot looks a bit odd because I only obtained a patch of data around each circle (the box) and it is doing a linear interpolation between those.
This is a one-time calibration so I’m happy to do some manual setting up work.
Thanks in advance!
Jack

This is how I display the contour:
figure(1)
pcolor(X,Y,P);
shading interp
hold on
colorbar
hold off

PS this is my first question so do say if there is anything I can improve for next time.This is not circle finding in an image, which has been well covered, but in an array.
I have an array P with several approximately-circular areas of a low value. I would like to find the centres of those areas to calibrate my device. Here is a contour 2D plot of P. The contour plot looks a bit odd because I only obtained a patch of data around each circle (the box) and it is doing a linear interpolation between those.
This is a one-time calibration so I’m happy to do some manual setting up work.
Thanks in advance!
Jack

This is how I display the contour:
figure(1)
pcolor(X,Y,P);
shading interp
hold on
colorbar
hold off

PS this is my first question so do say if there is anything I can improve for next time. This is not circle finding in an image, which has been well covered, but in an array.
I have an array P with several approximately-circular areas of a low value. I would like to find the centres of those areas to calibrate my device. Here is a contour 2D plot of P. The contour plot looks a bit odd because I only obtained a patch of data around each circle (the box) and it is doing a linear interpolation between those.
This is a one-time calibration so I’m happy to do some manual setting up work.
Thanks in advance!
Jack

This is how I display the contour:
figure(1)
pcolor(X,Y,P);
shading interp
hold on
colorbar
hold off

PS this is my first question so do say if there is anything I can improve for next time. circles, finding, arrays, variables, matlab MATLAB Answers — New Questions

​

Hello everyone,
This is a follow-up to an earlier question I had asked about capturing lossless images with Matlab. Earlier, I was using USB Webcam Package’s snapshot() function to capture, yet it seemed that there was some compression going on possibly because it was not possible to access YUY2 (I am not sure if this is relevant as I want to capture images rather than recording videos). Now I have moved on to use the Image Acquisition Toolbox and the interface generated the following code to capture images:
v = videoinput("winvideo", 1, "YUY2_3840x2160"); % Video device
v.ReturnedColorspace = "RGB";
src = getselectedsource(v);
src.Exposure = 0; % Camera parameters

image1 = getsnapshot(v); % Capturing the image

filename = "snapshot1.bmp"; % I changed the code to save the image as .bmp
imwrite(image1, filename, "bmp"); % Saving the file
Now the code is using the getsnapshot() function instead. Should this apply any additional compression on Matlab’s side of things? I know that the camera may do something but I want to ensure that Matlab does not.Hello everyone,
This is a follow-up to an earlier question I had asked about capturing lossless images with Matlab. Earlier, I was using USB Webcam Package’s snapshot() function to capture, yet it seemed that there was some compression going on possibly because it was not possible to access YUY2 (I am not sure if this is relevant as I want to capture images rather than recording videos). Now I have moved on to use the Image Acquisition Toolbox and the interface generated the following code to capture images:
v = videoinput("winvideo", 1, "YUY2_3840x2160"); % Video device
v.ReturnedColorspace = "RGB";
src = getselectedsource(v);
src.Exposure = 0; % Camera parameters

image1 = getsnapshot(v); % Capturing the image

filename = "snapshot1.bmp"; % I changed the code to save the image as .bmp
imwrite(image1, filename, "bmp"); % Saving the file
Now the code is using the getsnapshot() function instead. Should this apply any additional compression on Matlab’s side of things? I know that the camera may do something but I want to ensure that Matlab does not. Hello everyone,
This is a follow-up to an earlier question I had asked about capturing lossless images with Matlab. Earlier, I was using USB Webcam Package’s snapshot() function to capture, yet it seemed that there was some compression going on possibly because it was not possible to access YUY2 (I am not sure if this is relevant as I want to capture images rather than recording videos). Now I have moved on to use the Image Acquisition Toolbox and the interface generated the following code to capture images:
v = videoinput("winvideo", 1, "YUY2_3840x2160"); % Video device
v.ReturnedColorspace = "RGB";
src = getselectedsource(v);
src.Exposure = 0; % Camera parameters

image1 = getsnapshot(v); % Capturing the image

filename = "snapshot1.bmp"; % I changed the code to save the image as .bmp
imwrite(image1, filename, "bmp"); % Saving the file
Now the code is using the getsnapshot() function instead. Should this apply any additional compression on Matlab’s side of things? I know that the camera may do something but I want to ensure that Matlab does not. image acquisition, lossless image, bitmap, camera, recording, video, image MATLAB Answers — New Questions

​

Hi,
I have developed a function to be converted into exe file, the function include optimizer fmincon. The function is working well from matlab but when I converted into exe file using Application complier and start to run the exe file, the optimizer fmincon have this error "array indices must be positive integers or logical values".
Not sure what is wrong. Any help.Hi,
I have developed a function to be converted into exe file, the function include optimizer fmincon. The function is working well from matlab but when I converted into exe file using Application complier and start to run the exe file, the optimizer fmincon have this error "array indices must be positive integers or logical values".
Not sure what is wrong. Any help. Hi,
I have developed a function to be converted into exe file, the function include optimizer fmincon. The function is working well from matlab but when I converted into exe file using Application complier and start to run the exe file, the optimizer fmincon have this error "array indices must be positive integers or logical values".
Not sure what is wrong. Any help. application complier, fmincon, array indices must be positive integers or logical MATLAB Answers — New Questions

​

I have written a script to find the maximum and minimum values of 4 time series and then truncate each time series to these values as they are all of different length.
I want it to record the maximum and minimum values of all the time series first (lines 15-19), then after that store the overall smallest and largest values to new variables (lines 20-23).
At the moment, its constantly updating variables as it loops through, so its not using the overall smallest/largest values to truncate the time series.
I have tried putting lines 15-19 in another loop so it executes this first, but it doesnt seem to make any difference. Can anybody help?
%import all the csv files in the folder
csvFiles = dir(fullfile(folderPath, ‘*.csv’));
%read in all the csv files
for i = 1:length(csvFiles)
%get the individual file pathway
csvFilePath = fullfile(folderPath, csvFiles(i).name);
%read the file in
data = readmatrix(csvFilePath);
%remove nan’s from the timeseries
data = data(~any(isnan(data), 2), :);
%remove non-unique datapoints from the timeseries
[~, id] = unique(data(:,1)) ;
data = data(id,:);
for a = 1:length(csvFiles)
%find and save the maximum value of all the time series
maxVal(1) = max(data(:,1));
%find and save the minimum value of all the time series
minVal(1) = min(data(:,1));
%find and save the mean dt of all the time series
dt(1) = mean(diff(data(:,1)));
end
%find the time series that ends soonest
smallestMaxValue = min(maxVal)
%find the time series that starts latest
largestMinValue = max(minVal)
%truncate all the time series to the shortest one
truncateRow = find(data(:,1) > smallestMaxValue, 1, ‘first’); %find the index of the first value in the first column when the shortest time series is exceeded
if ~isempty(truncateRow)
truncatedData = data(1:truncateRow-1, :); %if there is a value in truncateRow, then truncate the dataset up to this point
else
truncatedData = data; %if there is no value in truncateRow (e.g. shortest time series), then leave the data as it is
end
endI have written a script to find the maximum and minimum values of 4 time series and then truncate each time series to these values as they are all of different length.
I want it to record the maximum and minimum values of all the time series first (lines 15-19), then after that store the overall smallest and largest values to new variables (lines 20-23).
At the moment, its constantly updating variables as it loops through, so its not using the overall smallest/largest values to truncate the time series.
I have tried putting lines 15-19 in another loop so it executes this first, but it doesnt seem to make any difference. Can anybody help?
%import all the csv files in the folder
csvFiles = dir(fullfile(folderPath, ‘*.csv’));
%read in all the csv files
for i = 1:length(csvFiles)
%get the individual file pathway
csvFilePath = fullfile(folderPath, csvFiles(i).name);
%read the file in
data = readmatrix(csvFilePath);
%remove nan’s from the timeseries
data = data(~any(isnan(data), 2), :);
%remove non-unique datapoints from the timeseries
[~, id] = unique(data(:,1)) ;
data = data(id,:);
for a = 1:length(csvFiles)
%find and save the maximum value of all the time series
maxVal(1) = max(data(:,1));
%find and save the minimum value of all the time series
minVal(1) = min(data(:,1));
%find and save the mean dt of all the time series
dt(1) = mean(diff(data(:,1)));
end
%find the time series that ends soonest
smallestMaxValue = min(maxVal)
%find the time series that starts latest
largestMinValue = max(minVal)
%truncate all the time series to the shortest one
truncateRow = find(data(:,1) > smallestMaxValue, 1, ‘first’); %find the index of the first value in the first column when the shortest time series is exceeded
if ~isempty(truncateRow)
truncatedData = data(1:truncateRow-1, :); %if there is a value in truncateRow, then truncate the dataset up to this point
else
truncatedData = data; %if there is no value in truncateRow (e.g. shortest time series), then leave the data as it is
end
end I have written a script to find the maximum and minimum values of 4 time series and then truncate each time series to these values as they are all of different length.
I want it to record the maximum and minimum values of all the time series first (lines 15-19), then after that store the overall smallest and largest values to new variables (lines 20-23).
At the moment, its constantly updating variables as it loops through, so its not using the overall smallest/largest values to truncate the time series.
I have tried putting lines 15-19 in another loop so it executes this first, but it doesnt seem to make any difference. Can anybody help?
%import all the csv files in the folder
csvFiles = dir(fullfile(folderPath, ‘*.csv’));
%read in all the csv files
for i = 1:length(csvFiles)
%get the individual file pathway
csvFilePath = fullfile(folderPath, csvFiles(i).name);
%read the file in
data = readmatrix(csvFilePath);
%remove nan’s from the timeseries
data = data(~any(isnan(data), 2), :);
%remove non-unique datapoints from the timeseries
[~, id] = unique(data(:,1)) ;
data = data(id,:);
for a = 1:length(csvFiles)
%find and save the maximum value of all the time series
maxVal(1) = max(data(:,1));
%find and save the minimum value of all the time series
minVal(1) = min(data(:,1));
%find and save the mean dt of all the time series
dt(1) = mean(diff(data(:,1)));
end
%find the time series that ends soonest
smallestMaxValue = min(maxVal)
%find the time series that starts latest
largestMinValue = max(minVal)
%truncate all the time series to the shortest one
truncateRow = find(data(:,1) > smallestMaxValue, 1, ‘first’); %find the index of the first value in the first column when the shortest time series is exceeded
if ~isempty(truncateRow)
truncatedData = data(1:truncateRow-1, :); %if there is a value in truncateRow, then truncate the dataset up to this point
else
truncatedData = data; %if there is no value in truncateRow (e.g. shortest time series), then leave the data as it is
end
end for loop, loop, nested loop MATLAB Answers — New Questions

​

Note: Workaround is to remove .NET 9.0 from PC to resolve conflicts with 6.0.
This might be a .NET issue as a whole, but I only see it using Matlab, so I am posting here to help others out facing the same issues.
I have a .dll from one of the groups I work with for communicating to our devices. The .dll was built in .NET 6.0 (core) (x64). I have been able to use it in the past in Matlab, but have now run into issues since installing Visual Studio 2022. It was discovered that Matlab would reference the most recent installation of .NET (9.0 in my case) which was installed by VS 2022. When I set "core" as the environment in Matlab (dotnetenv("core")), I would then make the .NET assembly visible to Matlab using NET.addAssembly("insert path here"). When Matlab got to this step, it would buffer for about 10 seconds then crash immediately with no crash report. Getting help from my local IT, we pin pointed it to the .NET 9.0 install causing the problem.
To get around this, you can either uninstall 9.0 or set up an environment variable in your system properties called "DOTNET_ROOT" that can force a path to be referenced.
So I would like to ask if anyone else has faced this issue in Matlab? Is it an unexpected error that needs an error handle? I am naive to .net, and really only know the particular dll I interact with to do my methods, etc.Note: Workaround is to remove .NET 9.0 from PC to resolve conflicts with 6.0.
This might be a .NET issue as a whole, but I only see it using Matlab, so I am posting here to help others out facing the same issues.
I have a .dll from one of the groups I work with for communicating to our devices. The .dll was built in .NET 6.0 (core) (x64). I have been able to use it in the past in Matlab, but have now run into issues since installing Visual Studio 2022. It was discovered that Matlab would reference the most recent installation of .NET (9.0 in my case) which was installed by VS 2022. When I set "core" as the environment in Matlab (dotnetenv("core")), I would then make the .NET assembly visible to Matlab using NET.addAssembly("insert path here"). When Matlab got to this step, it would buffer for about 10 seconds then crash immediately with no crash report. Getting help from my local IT, we pin pointed it to the .NET 9.0 install causing the problem.
To get around this, you can either uninstall 9.0 or set up an environment variable in your system properties called "DOTNET_ROOT" that can force a path to be referenced.
So I would like to ask if anyone else has faced this issue in Matlab? Is it an unexpected error that needs an error handle? I am naive to .net, and really only know the particular dll I interact with to do my methods, etc. Note: Workaround is to remove .NET 9.0 from PC to resolve conflicts with 6.0.
This might be a .NET issue as a whole, but I only see it using Matlab, so I am posting here to help others out facing the same issues.
I have a .dll from one of the groups I work with for communicating to our devices. The .dll was built in .NET 6.0 (core) (x64). I have been able to use it in the past in Matlab, but have now run into issues since installing Visual Studio 2022. It was discovered that Matlab would reference the most recent installation of .NET (9.0 in my case) which was installed by VS 2022. When I set "core" as the environment in Matlab (dotnetenv("core")), I would then make the .NET assembly visible to Matlab using NET.addAssembly("insert path here"). When Matlab got to this step, it would buffer for about 10 seconds then crash immediately with no crash report. Getting help from my local IT, we pin pointed it to the .NET 9.0 install causing the problem.
To get around this, you can either uninstall 9.0 or set up an environment variable in your system properties called "DOTNET_ROOT" that can force a path to be referenced.
So I would like to ask if anyone else has faced this issue in Matlab? Is it an unexpected error that needs an error handle? I am naive to .net, and really only know the particular dll I interact with to do my methods, etc. .net MATLAB Answers — New Questions

​

Hello everyone! Can I have some files about VPP Virtual Power Plants research for reference during my studies? Please help me.Hello everyone! Can I have some files about VPP Virtual Power Plants research for reference during my studies? Please help me. Hello everyone! Can I have some files about VPP Virtual Power Plants research for reference during my studies? Please help me. vpp, model MATLAB Answers — New Questions

​

I defined equality and inequality constraints and for binary variables I used IntCon, But then ga gives error that equality constraints cannot used with integer. But I need equality and inequality constraints with binary variables to get satisfy result.
If anyone know, how to used both constraints with binary variables and integer please tell me.I defined equality and inequality constraints and for binary variables I used IntCon, But then ga gives error that equality constraints cannot used with integer. But I need equality and inequality constraints with binary variables to get satisfy result.
If anyone know, how to used both constraints with binary variables and integer please tell me. I defined equality and inequality constraints and for binary variables I used IntCon, But then ga gives error that equality constraints cannot used with integer. But I need equality and inequality constraints with binary variables to get satisfy result.
If anyone know, how to used both constraints with binary variables and integer please tell me. binary variables with equality constraints, integer variables with equality constraints MATLAB Answers — New Questions

​

I am making a program to acheive delay and sum beamforming,
I looked for examples of this online and found one relatable. The code is given below. When i run the program i get this error
%% Examples on delay-and-sum response for different arrays and input signals

%% 1D-array case

% Create vectors of x- and y-coordinates of microphone positions
xPos = -0.8:0.2:0.8; % 1xP vector of x-positions [m]
yPos = zeros(1, numel(xPos)); % 1xP vector of y-positions [m]
zPos = zeros(1, numel(xPos));
elementWeights = ones(1, numel(xPos))/numel(xPos); % 1xP vector of weightings

% Define arriving angles and frequency of input signals
thetaArrivalAngles = [-30 10]; % degrees
phiArrivalAngles = [0 0]; % degrees
f = 800; % [Hz]
c = 340; % [m/s]
fs = 44.1e3; % [Hz]

% Define array scanning angles (1D, so phi = 0)
thetaScanAngles = -90:0.1:90; % degrees
phiScanAngles = 0; % degrees

% Create input signal
inputSignal = createSignal(xPos, yPos, zPos, f, c, fs, thetaArrivalAngles, phiArrivalAngles);

% Create steering vector/matrix
e = steeringVector(xPos, yPos, zPos, f, c, thetaScanAngles, phiScanAngles);

% Create cross spectral matrix
R = crossSpectralMatrix(inputSignal);

% Calculate delay-and-sum steered response
S = steeredResponseDelayAndSum(R, e, elementWeights);

%Normalise spectrum
spectrumNormalized = abs(S)/max(abs(S));

%Convert to decibel
spectrumLog = 10*log10(spectrumNormalized);

%Plot array
fig1 = figure;
fig1.Color = ‘w’;
ax = axes(‘Parent’, fig1);
scatter(ax, xPos, yPos, 20, ‘filled’)
axis(ax, ‘square’)
ax.XLim = [-1 1];
ax.YLim = [-1 1];
grid(ax, ‘on’)
title(ax, ‘Microphone positions’)

%Plot steered response with indicator lines
fig2 = figure;
fig2.Color = ‘w’;
ax = axes(‘Parent’, fig2);
plot(ax, thetaScanAngles, spectrumLog)
grid(ax, ‘on’)
ax.XLim = [thetaScanAngles(1) thetaScanAngles(end)];

for j=1:numel(thetaArrivalAngles)
indx = find(thetaScanAngles >= thetaArrivalAngles(j), 1);
line(ax, [thetaScanAngles(indx) thetaScanAngles(indx)], ax.YLim,’LineWidth’, 1, ‘Color’, ‘r’, ‘LineStyle’, ‘–‘);
end
xlabel(ax, ‘theta’)
ylabel(ax, ‘dB’)I am making a program to acheive delay and sum beamforming,
I looked for examples of this online and found one relatable. The code is given below. When i run the program i get this error
%% Examples on delay-and-sum response for different arrays and input signals

%% 1D-array case

% Create vectors of x- and y-coordinates of microphone positions
xPos = -0.8:0.2:0.8; % 1xP vector of x-positions [m]
yPos = zeros(1, numel(xPos)); % 1xP vector of y-positions [m]
zPos = zeros(1, numel(xPos));
elementWeights = ones(1, numel(xPos))/numel(xPos); % 1xP vector of weightings

% Define arriving angles and frequency of input signals
thetaArrivalAngles = [-30 10]; % degrees
phiArrivalAngles = [0 0]; % degrees
f = 800; % [Hz]
c = 340; % [m/s]
fs = 44.1e3; % [Hz]

% Define array scanning angles (1D, so phi = 0)
thetaScanAngles = -90:0.1:90; % degrees
phiScanAngles = 0; % degrees

% Create input signal
inputSignal = createSignal(xPos, yPos, zPos, f, c, fs, thetaArrivalAngles, phiArrivalAngles);

% Create steering vector/matrix
e = steeringVector(xPos, yPos, zPos, f, c, thetaScanAngles, phiScanAngles);

% Create cross spectral matrix
R = crossSpectralMatrix(inputSignal);

% Calculate delay-and-sum steered response
S = steeredResponseDelayAndSum(R, e, elementWeights);

%Normalise spectrum
spectrumNormalized = abs(S)/max(abs(S));

%Convert to decibel
spectrumLog = 10*log10(spectrumNormalized);

%Plot array
fig1 = figure;
fig1.Color = ‘w’;
ax = axes(‘Parent’, fig1);
scatter(ax, xPos, yPos, 20, ‘filled’)
axis(ax, ‘square’)
ax.XLim = [-1 1];
ax.YLim = [-1 1];
grid(ax, ‘on’)
title(ax, ‘Microphone positions’)

%Plot steered response with indicator lines
fig2 = figure;
fig2.Color = ‘w’;
ax = axes(‘Parent’, fig2);
plot(ax, thetaScanAngles, spectrumLog)
grid(ax, ‘on’)
ax.XLim = [thetaScanAngles(1) thetaScanAngles(end)];

for j=1:numel(thetaArrivalAngles)
indx = find(thetaScanAngles >= thetaArrivalAngles(j), 1);
line(ax, [thetaScanAngles(indx) thetaScanAngles(indx)], ax.YLim,’LineWidth’, 1, ‘Color’, ‘r’, ‘LineStyle’, ‘–‘);
end
xlabel(ax, ‘theta’)
ylabel(ax, ‘dB’) I am making a program to acheive delay and sum beamforming,
I looked for examples of this online and found one relatable. The code is given below. When i run the program i get this error
%% Examples on delay-and-sum response for different arrays and input signals

%% 1D-array case

% Create vectors of x- and y-coordinates of microphone positions
xPos = -0.8:0.2:0.8; % 1xP vector of x-positions [m]
yPos = zeros(1, numel(xPos)); % 1xP vector of y-positions [m]
zPos = zeros(1, numel(xPos));
elementWeights = ones(1, numel(xPos))/numel(xPos); % 1xP vector of weightings

% Define arriving angles and frequency of input signals
thetaArrivalAngles = [-30 10]; % degrees
phiArrivalAngles = [0 0]; % degrees
f = 800; % [Hz]
c = 340; % [m/s]
fs = 44.1e3; % [Hz]

% Define array scanning angles (1D, so phi = 0)
thetaScanAngles = -90:0.1:90; % degrees
phiScanAngles = 0; % degrees

% Create input signal
inputSignal = createSignal(xPos, yPos, zPos, f, c, fs, thetaArrivalAngles, phiArrivalAngles);

% Create steering vector/matrix
e = steeringVector(xPos, yPos, zPos, f, c, thetaScanAngles, phiScanAngles);

% Create cross spectral matrix
R = crossSpectralMatrix(inputSignal);

% Calculate delay-and-sum steered response
S = steeredResponseDelayAndSum(R, e, elementWeights);

%Normalise spectrum
spectrumNormalized = abs(S)/max(abs(S));

%Convert to decibel
spectrumLog = 10*log10(spectrumNormalized);

%Plot array
fig1 = figure;
fig1.Color = ‘w’;
ax = axes(‘Parent’, fig1);
scatter(ax, xPos, yPos, 20, ‘filled’)
axis(ax, ‘square’)
ax.XLim = [-1 1];
ax.YLim = [-1 1];
grid(ax, ‘on’)
title(ax, ‘Microphone positions’)

%Plot steered response with indicator lines
fig2 = figure;
fig2.Color = ‘w’;
ax = axes(‘Parent’, fig2);
plot(ax, thetaScanAngles, spectrumLog)
grid(ax, ‘on’)
ax.XLim = [thetaScanAngles(1) thetaScanAngles(end)];

for j=1:numel(thetaArrivalAngles)
indx = find(thetaScanAngles >= thetaArrivalAngles(j), 1);
line(ax, [thetaScanAngles(indx) thetaScanAngles(indx)], ax.YLim,’LineWidth’, 1, ‘Color’, ‘r’, ‘LineStyle’, ‘–‘);
end
xlabel(ax, ‘theta’)
ylabel(ax, ‘dB’) digital signal processing MATLAB Answers — New Questions

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