How do I set up MATLAB Web Server using Apache as an httpd server on Windows NT?How do I set up MATLAB Web Server using Apache as an httpd server on Windows NT? How do I set up MATLAB Web Server using Apache as an httpd server on Windows NT? apache, windows, nt, web, server MATLAB Answers — New Questions

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clear all
close all
clc
tic

L=10; %[m] Fiber length
PS=1;
n=1.45;
eps0=8.854e-12; % [F/m] Vacuum permittivity
mu0 = 4*pi*1e-7;%[H/m] Vacuum permeability
c=2.9979e8; % [m/sec] Speed of light
Z0=sqrt(mu0/eps0); %[Ohm] Vacuum impedance
dt = 6e-12; dz=dt*c/n; %Spacial and Temporal step sizes.
%dz=2.5e-4;
Fs=1/dt;

N=round(L/dz); % Fiber length discretization

T=10*2*L*n/c; %time taken for 10 round trips
Nt=round(T/dt);
%% material characteristics

A=80e-12; %[m^2] fiber’s effective area

I1_0=PS/A;

% figure;
FA=(-Nt/2:Nt/2-1)*Fs/Nt;

fc=3e9;
X = randn(1,Nt); %random noise generation
Y1 = 10*lowpass(X, fc, Fs, Steepness=0.8);

ypm1 = 1.2743e+06*exp(1i*Y1);
figure;
plot(FA,abs(fftshift(fft(Y1/Nt))));
xlim([-20e9 20

e9]);
figure;
semilogy(FA,(2*n*c*eps0*A*abs(fftshift(fft(ypm1/Nt).^2))))

I am trying to generate White noise source for my phase modulation technique.
The procedure is to pass the signal through a rectangular band filter to imprint the sinc envelope onto the waveform.
Likewise I have generated random noise and passed through low pass filter of 3GHz but the fft of the product is not upto the figure.
Can anyone suggest any changes.clear all
close all
clc
tic

L=10; %[m] Fiber length
PS=1;
n=1.45;
eps0=8.854e-12; % [F/m] Vacuum permittivity
mu0 = 4*pi*1e-7;%[H/m] Vacuum permeability
c=2.9979e8; % [m/sec] Speed of light
Z0=sqrt(mu0/eps0); %[Ohm] Vacuum impedance
dt = 6e-12; dz=dt*c/n; %Spacial and Temporal step sizes.
%dz=2.5e-4;
Fs=1/dt;

N=round(L/dz); % Fiber length discretization

T=10*2*L*n/c; %time taken for 10 round trips
Nt=round(T/dt);
%% material characteristics

A=80e-12; %[m^2] fiber’s effective area

I1_0=PS/A;

% figure;
FA=(-Nt/2:Nt/2-1)*Fs/Nt;

fc=3e9;
X = randn(1,Nt); %random noise generation
Y1 = 10*lowpass(X, fc, Fs, Steepness=0.8);

ypm1 = 1.2743e+06*exp(1i*Y1);
figure;
plot(FA,abs(fftshift(fft(Y1/Nt))));
xlim([-20e9 20

e9]);
figure;
semilogy(FA,(2*n*c*eps0*A*abs(fftshift(fft(ypm1/Nt).^2))))

I am trying to generate White noise source for my phase modulation technique.
The procedure is to pass the signal through a rectangular band filter to imprint the sinc envelope onto the waveform.
Likewise I have generated random noise and passed through low pass filter of 3GHz but the fft of the product is not upto the figure.
Can anyone suggest any changes. clear all
close all
clc
tic

L=10; %[m] Fiber length
PS=1;
n=1.45;
eps0=8.854e-12; % [F/m] Vacuum permittivity
mu0 = 4*pi*1e-7;%[H/m] Vacuum permeability
c=2.9979e8; % [m/sec] Speed of light
Z0=sqrt(mu0/eps0); %[Ohm] Vacuum impedance
dt = 6e-12; dz=dt*c/n; %Spacial and Temporal step sizes.
%dz=2.5e-4;
Fs=1/dt;

N=round(L/dz); % Fiber length discretization

T=10*2*L*n/c; %time taken for 10 round trips
Nt=round(T/dt);
%% material characteristics

A=80e-12; %[m^2] fiber’s effective area

I1_0=PS/A;

% figure;
FA=(-Nt/2:Nt/2-1)*Fs/Nt;

fc=3e9;
X = randn(1,Nt); %random noise generation
Y1 = 10*lowpass(X, fc, Fs, Steepness=0.8);

ypm1 = 1.2743e+06*exp(1i*Y1);
figure;
plot(FA,abs(fftshift(fft(Y1/Nt))));
xlim([-20e9 20

e9]);
figure;
semilogy(FA,(2*n*c*eps0*A*abs(fftshift(fft(ypm1/Nt).^2))))

I am trying to generate White noise source for my phase modulation technique.
The procedure is to pass the signal through a rectangular band filter to imprint the sinc envelope onto the waveform.
Likewise I have generated random noise and passed through low pass filter of 3GHz but the fft of the product is not upto the figure.
Can anyone suggest any changes. wns, fft, sinc MATLAB Answers — New Questions

​

Hello,
I’m testing a MATLAB script on a SIMULMINK model made of 1727 models, migrated from M2016b environment to M2022b environment.
The purpose of the script is to build a predecessor list for each model while analyzing the connections of the signals.
I’ve noticed the computation time to retrieve the list of input signals from BusSelector blocks has highly increased from M20163b to M2022b
With profiler, the following function
bus = get_param(handle, ‘InputSignals’);
can take 70-90 sec sometimes whereas it was never exceeding 1s before (M2016b).
Please see the screenshots from profiler

Is there any reason why this computation time can increase so much, and what king of workaround can I test.
As I’m analyzing the list of predecessors from each model inports, if I find a busSelector, I’m analyzing the signal names to compute the indexes within the bus structure where my signal is located in order to apply the same indexes when I meet the corresponding BusCreator blocks to continue the ascending propagation analysis.Hello,
I’m testing a MATLAB script on a SIMULMINK model made of 1727 models, migrated from M2016b environment to M2022b environment.
The purpose of the script is to build a predecessor list for each model while analyzing the connections of the signals.
I’ve noticed the computation time to retrieve the list of input signals from BusSelector blocks has highly increased from M20163b to M2022b
With profiler, the following function
bus = get_param(handle, ‘InputSignals’);
can take 70-90 sec sometimes whereas it was never exceeding 1s before (M2016b).
Please see the screenshots from profiler

Is there any reason why this computation time can increase so much, and what king of workaround can I test.
As I’m analyzing the list of predecessors from each model inports, if I find a busSelector, I’m analyzing the signal names to compute the indexes within the bus structure where my signal is located in order to apply the same indexes when I meet the corresponding BusCreator blocks to continue the ascending propagation analysis. Hello,
I’m testing a MATLAB script on a SIMULMINK model made of 1727 models, migrated from M2016b environment to M2022b environment.
The purpose of the script is to build a predecessor list for each model while analyzing the connections of the signals.
I’ve noticed the computation time to retrieve the list of input signals from BusSelector blocks has highly increased from M20163b to M2022b
With profiler, the following function
bus = get_param(handle, ‘InputSignals’);
can take 70-90 sec sometimes whereas it was never exceeding 1s before (M2016b).
Please see the screenshots from profiler

Is there any reason why this computation time can increase so much, and what king of workaround can I test.
As I’m analyzing the list of predecessors from each model inports, if I find a busSelector, I’m analyzing the signal names to compute the indexes within the bus structure where my signal is located in order to apply the same indexes when I meet the corresponding BusCreator blocks to continue the ascending propagation analysis. busselector, signal processing, time MATLAB Answers — New Questions

​

I want to connect my model to a2l variables in my test ECU through XCP on CAN. My XCP transmit address is 0x200 and XCP receive address is 0x300. I do not understand how to use the XCP Transport Layer block from Simulink Real-time.
I have created a model using the blocks shown in the Screenshot. However, I get errors shown in the attached images when I run the model – MAX_CTO from the Connect response (80) and MAX_DTO from the Connect response (2) does not match the value from the A2L (8). I’m not sure if there are any other settings to be configured in the model.I want to connect my model to a2l variables in my test ECU through XCP on CAN. My XCP transmit address is 0x200 and XCP receive address is 0x300. I do not understand how to use the XCP Transport Layer block from Simulink Real-time.
I have created a model using the blocks shown in the Screenshot. However, I get errors shown in the attached images when I run the model – MAX_CTO from the Connect response (80) and MAX_DTO from the Connect response (2) does not match the value from the A2L (8). I’m not sure if there are any other settings to be configured in the model. I want to connect my model to a2l variables in my test ECU through XCP on CAN. My XCP transmit address is 0x200 and XCP receive address is 0x300. I do not understand how to use the XCP Transport Layer block from Simulink Real-time.
I have created a model using the blocks shown in the Screenshot. However, I get errors shown in the attached images when I run the model – MAX_CTO from the Connect response (80) and MAX_DTO from the Connect response (2) does not match the value from the A2L (8). I’m not sure if there are any other settings to be configured in the model. xcp on can, xcp can transport layer block, ecu a2l read and write MATLAB Answers — New Questions

​

Hi all,
I have a matrix that has two columns as following:
A = [0.1 0.1 ; 0.1 -0.3 ; 0.1 0.5 ; 0.1 0; 0.1 -0.5; 0.1 -0.1; 0.1 0.4;
0.2 0.1 ; 0.2 -0.3 ; 0.2 0.5 ; 0.2 0; 0.2 -0.5; 0.2 -0.1; 0.2 0.4;
0.3 0.1 ; 0.3 -0.3 ; 0.3 0.5 ; 0.3 0; 0.3 -0.5; 0.3 -0.1; 0.3 0.4];
And I want to sort the second column of this matrix for every uniqe value of the first column so that the result looks like:
Asorted = [0.1 -0.5 ; 0.1 -0.3 ; 0.1 -0.1 ; 0.1 0; 0.1 0.1; 0.1 0.4; 0.1 0.5;
0.2 -0.5 ; 0.2 -0.3 ; 0.2 -0.1 ; 0.2 0; 0.2 0.1; 0.2 0.4; 0.2 0.5;
0.3 -0.5 ; 0.3 -0.3 ; 0.3 -0.1 ; 0.3 0; 0.3 0.1; 0.3 0.4; 0.3 0.5];
My "failing" attempt of doing this is the following:
A1 = A(:,1); %forst column
A2 = A(:,2); %second column
Auni = unique(A1); %unique value of the first column

for i = 1:size(A,1) %go through all the points in the first column
for j = 1:numel(Auni) %go throguh the unique values of the first column
if A1(i) == Auni(j) %if the point equals one of the uniqe values
[A2 , sortdx] = sort(A2); %sort out the second column of matrix A
A1 = A1(sortidx); %sort the first column accordingly
Asorted = [A1 A2]; %combine both results.
end
end
end
Also, how can I reorder another matrix based on the sorting done previously on matrix ?
Any help would be appreicted.
Thanks.Hi all,
I have a matrix that has two columns as following:
A = [0.1 0.1 ; 0.1 -0.3 ; 0.1 0.5 ; 0.1 0; 0.1 -0.5; 0.1 -0.1; 0.1 0.4;
0.2 0.1 ; 0.2 -0.3 ; 0.2 0.5 ; 0.2 0; 0.2 -0.5; 0.2 -0.1; 0.2 0.4;
0.3 0.1 ; 0.3 -0.3 ; 0.3 0.5 ; 0.3 0; 0.3 -0.5; 0.3 -0.1; 0.3 0.4];
And I want to sort the second column of this matrix for every uniqe value of the first column so that the result looks like:
Asorted = [0.1 -0.5 ; 0.1 -0.3 ; 0.1 -0.1 ; 0.1 0; 0.1 0.1; 0.1 0.4; 0.1 0.5;
0.2 -0.5 ; 0.2 -0.3 ; 0.2 -0.1 ; 0.2 0; 0.2 0.1; 0.2 0.4; 0.2 0.5;
0.3 -0.5 ; 0.3 -0.3 ; 0.3 -0.1 ; 0.3 0; 0.3 0.1; 0.3 0.4; 0.3 0.5];
My "failing" attempt of doing this is the following:
A1 = A(:,1); %forst column
A2 = A(:,2); %second column
Auni = unique(A1); %unique value of the first column

for i = 1:size(A,1) %go through all the points in the first column
for j = 1:numel(Auni) %go throguh the unique values of the first column
if A1(i) == Auni(j) %if the point equals one of the uniqe values
[A2 , sortdx] = sort(A2); %sort out the second column of matrix A
A1 = A1(sortidx); %sort the first column accordingly
Asorted = [A1 A2]; %combine both results.
end
end
end
Also, how can I reorder another matrix based on the sorting done previously on matrix ?
Any help would be appreicted.
Thanks. Hi all,
I have a matrix that has two columns as following:
A = [0.1 0.1 ; 0.1 -0.3 ; 0.1 0.5 ; 0.1 0; 0.1 -0.5; 0.1 -0.1; 0.1 0.4;
0.2 0.1 ; 0.2 -0.3 ; 0.2 0.5 ; 0.2 0; 0.2 -0.5; 0.2 -0.1; 0.2 0.4;
0.3 0.1 ; 0.3 -0.3 ; 0.3 0.5 ; 0.3 0; 0.3 -0.5; 0.3 -0.1; 0.3 0.4];
And I want to sort the second column of this matrix for every uniqe value of the first column so that the result looks like:
Asorted = [0.1 -0.5 ; 0.1 -0.3 ; 0.1 -0.1 ; 0.1 0; 0.1 0.1; 0.1 0.4; 0.1 0.5;
0.2 -0.5 ; 0.2 -0.3 ; 0.2 -0.1 ; 0.2 0; 0.2 0.1; 0.2 0.4; 0.2 0.5;
0.3 -0.5 ; 0.3 -0.3 ; 0.3 -0.1 ; 0.3 0; 0.3 0.1; 0.3 0.4; 0.3 0.5];
My "failing" attempt of doing this is the following:
A1 = A(:,1); %forst column
A2 = A(:,2); %second column
Auni = unique(A1); %unique value of the first column

for i = 1:size(A,1) %go through all the points in the first column
for j = 1:numel(Auni) %go throguh the unique values of the first column
if A1(i) == Auni(j) %if the point equals one of the uniqe values
[A2 , sortdx] = sort(A2); %sort out the second column of matrix A
A1 = A1(sortidx); %sort the first column accordingly
Asorted = [A1 A2]; %combine both results.
end
end
end
Also, how can I reorder another matrix based on the sorting done previously on matrix ?
Any help would be appreicted.
Thanks. matlab, reorder, rows, matrices, index, indexing, sort MATLAB Answers — New Questions

​

meaning of this codemeaning of this code meaning of this code started with this code MATLAB Answers — New Questions

​

Hello all, I am working on research paper in which I have to implement Maximum Likelihood (ML) detection at the receiver. I am interested in plotting Bit error rate (BER) Vs Signal to noise ratio (SNR) plot using semilogy.
Below I am giving the expression of ML detection that I am trying to implement:
— (1)
where is received signal of dimension , is complex Gaussian channel matrix of dimension such that it has zero mean and 10 variance, is transmitted signal such that and each has dimension and is chosen from set , where has dimension and it denotes the GSSK modulated symbol. The GSSK modulated symbol has value 1 at positions and value 0 at the remaining () positions.

Also, and , where denotes the cardinality of a set. To find the optimal solution
of (1), the complexity of exhaustive search over is too high to implement.
My query is that I am not getting how to implement ML detection (eq. (1)) in MATLAB. I am also sharing the MATLAB code that I had developed for received signal which is given as
—-(2)
where is additive white Gaussian noise and has dimension .
Any help in this regard will be highly appreciated.
MATLAB code:
N_t = 4; % number of antennas at tag
N_r = 2; % number of antennas at reader
L = 500; % number of observations
n_t = 2; % number of active antennas in GSSK

% Define the GSSK symbols explicitly
GSSK_symbols = [
1 1 0 0;
1 0 1 0;
1 0 0 1;
0 0 1 1;
];

% Total information bits carried by each symbol
M = floor(log2(nchoosek(N_t, n_t)));

% Number of GSSK symbols
N = 2^M;

for snr = 0:3:21 % This is SNR in dB
% Generate the channel matrix H_tr
H_tr = sqrt(10/2) * (randn(N_r, N_t) + 1i*randn(N_r, N_t));

% Generate the transmitted signal X
X = zeros(N_t, L);
for l = 1:L
symbol_idx = randi(N); % randomly choose a symbol index
X(:, l) = GSSK_symbols(symbol_idx, :).’;
end

% Generate the noise W
W = (randn(N_r, L) + 1i*randn(N_r, L)) / sqrt(2);

% Calculate the received signal Y
Y = H_tr * X + 10^(-snr/20) * W;
endHello all, I am working on research paper in which I have to implement Maximum Likelihood (ML) detection at the receiver. I am interested in plotting Bit error rate (BER) Vs Signal to noise ratio (SNR) plot using semilogy.
Below I am giving the expression of ML detection that I am trying to implement:
— (1)
where is received signal of dimension , is complex Gaussian channel matrix of dimension such that it has zero mean and 10 variance, is transmitted signal such that and each has dimension and is chosen from set , where has dimension and it denotes the GSSK modulated symbol. The GSSK modulated symbol has value 1 at positions and value 0 at the remaining () positions.

Also, and , where denotes the cardinality of a set. To find the optimal solution
of (1), the complexity of exhaustive search over is too high to implement.
My query is that I am not getting how to implement ML detection (eq. (1)) in MATLAB. I am also sharing the MATLAB code that I had developed for received signal which is given as
—-(2)
where is additive white Gaussian noise and has dimension .
Any help in this regard will be highly appreciated.
MATLAB code:
N_t = 4; % number of antennas at tag
N_r = 2; % number of antennas at reader
L = 500; % number of observations
n_t = 2; % number of active antennas in GSSK

% Define the GSSK symbols explicitly
GSSK_symbols = [
1 1 0 0;
1 0 1 0;
1 0 0 1;
0 0 1 1;
];

% Total information bits carried by each symbol
M = floor(log2(nchoosek(N_t, n_t)));

% Number of GSSK symbols
N = 2^M;

for snr = 0:3:21 % This is SNR in dB
% Generate the channel matrix H_tr
H_tr = sqrt(10/2) * (randn(N_r, N_t) + 1i*randn(N_r, N_t));

% Generate the transmitted signal X
X = zeros(N_t, L);
for l = 1:L
symbol_idx = randi(N); % randomly choose a symbol index
X(:, l) = GSSK_symbols(symbol_idx, :).’;
end

% Generate the noise W
W = (randn(N_r, L) + 1i*randn(N_r, L)) / sqrt(2);

% Calculate the received signal Y
Y = H_tr * X + 10^(-snr/20) * W;
end Hello all, I am working on research paper in which I have to implement Maximum Likelihood (ML) detection at the receiver. I am interested in plotting Bit error rate (BER) Vs Signal to noise ratio (SNR) plot using semilogy.
Below I am giving the expression of ML detection that I am trying to implement:
— (1)
where is received signal of dimension , is complex Gaussian channel matrix of dimension such that it has zero mean and 10 variance, is transmitted signal such that and each has dimension and is chosen from set , where has dimension and it denotes the GSSK modulated symbol. The GSSK modulated symbol has value 1 at positions and value 0 at the remaining () positions.

Also, and , where denotes the cardinality of a set. To find the optimal solution
of (1), the complexity of exhaustive search over is too high to implement.
My query is that I am not getting how to implement ML detection (eq. (1)) in MATLAB. I am also sharing the MATLAB code that I had developed for received signal which is given as
—-(2)
where is additive white Gaussian noise and has dimension .
Any help in this regard will be highly appreciated.
MATLAB code:
N_t = 4; % number of antennas at tag
N_r = 2; % number of antennas at reader
L = 500; % number of observations
n_t = 2; % number of active antennas in GSSK

% Define the GSSK symbols explicitly
GSSK_symbols = [
1 1 0 0;
1 0 1 0;
1 0 0 1;
0 0 1 1;
];

% Total information bits carried by each symbol
M = floor(log2(nchoosek(N_t, n_t)));

% Number of GSSK symbols
N = 2^M;

for snr = 0:3:21 % This is SNR in dB
% Generate the channel matrix H_tr
H_tr = sqrt(10/2) * (randn(N_r, N_t) + 1i*randn(N_r, N_t));

% Generate the transmitted signal X
X = zeros(N_t, L);
for l = 1:L
symbol_idx = randi(N); % randomly choose a symbol index
X(:, l) = GSSK_symbols(symbol_idx, :).’;
end

% Generate the noise W
W = (randn(N_r, L) + 1i*randn(N_r, L)) / sqrt(2);

% Calculate the received signal Y
Y = H_tr * X + 10^(-snr/20) * W;
end digital signal processing, simulation, maximum likelihood MATLAB Answers — New Questions

​

[Roadrunner] Hi, I was wondering if it is possible to import roads into Roadrunner based on existing data of roads, etc. Is there a way to do this?
Thank you![Roadrunner] Hi, I was wondering if it is possible to import roads into Roadrunner based on existing data of roads, etc. Is there a way to do this?
Thank you! [Roadrunner] Hi, I was wondering if it is possible to import roads into Roadrunner based on existing data of roads, etc. Is there a way to do this?
Thank you! data import, geodata, gis, import roads, how to import, roadrunner MATLAB Answers — New Questions

​

Hello everyone,
I’m not really good at Matlab, but I need to use it to process some load cycles result using the rainflow function (please see attachment)

I have written the code as below
clear all,
clc,
[filename,pathname] = uigetfile({‘*.xlsx;*.xlsm’,’Excel Worksheets (*.xlsx,*.xlsm)’},’Select File’);
[file,sheets] = xlsfinfo([pathname,filename]);
num_1 = xlsread(filename);

[num_3, txt]= xlsread(filename);

%read only row and column with number
Data_1 = num_3(4:end,:); % 4:end, –> choose all the row start from 4 % : –> choose all the column % start at row 4 and read all column

X = num_3(4:end,7); % 4,–> Choose only row 4 seread oly row 4 and all column.
Y = num_3(4:end,6);
Z = num_3(4:end,8);

figure(1)

plot3(X,Y,Z);

t = linspace(min(Y),max(Y),length(Z)/10);
d = linspace(min(Y),max(Y),length(Z)/5);

figure(2)

Z = [X Y]

rainflow(Z,t);
and unfortunately have the errors below after the code:
Error using rainflow
Expected X to be a vector.

Error in rainflow>parseInputs (line 184)
validateattributes(x,{‘single’,’double’},…

Error in rainflow (line 81)
[x,t,ext,td] = parseInputs(x,varargin{:});

Error in KW31_BMW_Load_Cycle_Ju (line 39)
rainflow(Z,t)

Can someone please tell me were I´making the mytake by using the Rainflow function?

Thank in advanceHello everyone,
I’m not really good at Matlab, but I need to use it to process some load cycles result using the rainflow function (please see attachment)

I have written the code as below
clear all,
clc,
[filename,pathname] = uigetfile({‘*.xlsx;*.xlsm’,’Excel Worksheets (*.xlsx,*.xlsm)’},’Select File’);
[file,sheets] = xlsfinfo([pathname,filename]);
num_1 = xlsread(filename);

[num_3, txt]= xlsread(filename);

%read only row and column with number
Data_1 = num_3(4:end,:); % 4:end, –> choose all the row start from 4 % : –> choose all the column % start at row 4 and read all column

X = num_3(4:end,7); % 4,–> Choose only row 4 seread oly row 4 and all column.
Y = num_3(4:end,6);
Z = num_3(4:end,8);

figure(1)

plot3(X,Y,Z);

t = linspace(min(Y),max(Y),length(Z)/10);
d = linspace(min(Y),max(Y),length(Z)/5);

figure(2)

Z = [X Y]

rainflow(Z,t);
and unfortunately have the errors below after the code:
Error using rainflow
Expected X to be a vector.

Error in rainflow>parseInputs (line 184)
validateattributes(x,{‘single’,’double’},…

Error in rainflow (line 81)
[x,t,ext,td] = parseInputs(x,varargin{:});

Error in KW31_BMW_Load_Cycle_Ju (line 39)
rainflow(Z,t)

Can someone please tell me were I´making the mytake by using the Rainflow function?

Thank in advance Hello everyone,
I’m not really good at Matlab, but I need to use it to process some load cycles result using the rainflow function (please see attachment)

I have written the code as below
clear all,
clc,
[filename,pathname] = uigetfile({‘*.xlsx;*.xlsm’,’Excel Worksheets (*.xlsx,*.xlsm)’},’Select File’);
[file,sheets] = xlsfinfo([pathname,filename]);
num_1 = xlsread(filename);

[num_3, txt]= xlsread(filename);

%read only row and column with number
Data_1 = num_3(4:end,:); % 4:end, –> choose all the row start from 4 % : –> choose all the column % start at row 4 and read all column

X = num_3(4:end,7); % 4,–> Choose only row 4 seread oly row 4 and all column.
Y = num_3(4:end,6);
Z = num_3(4:end,8);

figure(1)

plot3(X,Y,Z);

t = linspace(min(Y),max(Y),length(Z)/10);
d = linspace(min(Y),max(Y),length(Z)/5);

figure(2)

Z = [X Y]

rainflow(Z,t);
and unfortunately have the errors below after the code:
Error using rainflow
Expected X to be a vector.

Error in rainflow>parseInputs (line 184)
validateattributes(x,{‘single’,’double’},…

Error in rainflow (line 81)
[x,t,ext,td] = parseInputs(x,varargin{:});

Error in KW31_BMW_Load_Cycle_Ju (line 39)
rainflow(Z,t)

Can someone please tell me were I´making the mytake by using the Rainflow function?

Thank in advance hello togheter i´m trying to plot a rainflow MATLAB Answers — New Questions

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Hi,
I was given a half range expansion function f(x) = 0, 0<x<2 and f(x) = 1, <2<x<4.
I was asked to solve for the Fourier cosine series and Fourier sine series and then plot each.
I solved by hand:
Fourier Cosine Series:
a0 = 1/2
an = -2/(n*pi)*sin((n*pi)/2)
f(x) = 1/2 + sum(an*cos((n*pi*x)/4)) from n =1 to infinity
Fourier Sine Series:
bn = [2/(n*pi)]*[(-1)^(n+1) + cos((n*pi)/2)]
f(x) = sum(bn*sin((n*pi*x)/4))
I’m fairly new to Matlab and very unexperienced, where I’m having dificulty is plotting these functions against x, say x = [-24 24] and n=1:1:50 or until square waves appear. I gained some experience plotting their partial sums using fplot, but that approach does not appear to work here. It isn’t feasible to plot the 50th partial sum. I’ve seen more arrayfun usage online, but I do not understand it whatsoever.
Any help and explanation would be greatly appreciated. Thanks in advance.Hi,
I was given a half range expansion function f(x) = 0, 0<x<2 and f(x) = 1, <2<x<4.
I was asked to solve for the Fourier cosine series and Fourier sine series and then plot each.
I solved by hand:
Fourier Cosine Series:
a0 = 1/2
an = -2/(n*pi)*sin((n*pi)/2)
f(x) = 1/2 + sum(an*cos((n*pi*x)/4)) from n =1 to infinity
Fourier Sine Series:
bn = [2/(n*pi)]*[(-1)^(n+1) + cos((n*pi)/2)]
f(x) = sum(bn*sin((n*pi*x)/4))
I’m fairly new to Matlab and very unexperienced, where I’m having dificulty is plotting these functions against x, say x = [-24 24] and n=1:1:50 or until square waves appear. I gained some experience plotting their partial sums using fplot, but that approach does not appear to work here. It isn’t feasible to plot the 50th partial sum. I’ve seen more arrayfun usage online, but I do not understand it whatsoever.
Any help and explanation would be greatly appreciated. Thanks in advance. Hi,
I was given a half range expansion function f(x) = 0, 0<x<2 and f(x) = 1, <2<x<4.
I was asked to solve for the Fourier cosine series and Fourier sine series and then plot each.
I solved by hand:
Fourier Cosine Series:
a0 = 1/2
an = -2/(n*pi)*sin((n*pi)/2)
f(x) = 1/2 + sum(an*cos((n*pi*x)/4)) from n =1 to infinity
Fourier Sine Series:
bn = [2/(n*pi)]*[(-1)^(n+1) + cos((n*pi)/2)]
f(x) = sum(bn*sin((n*pi*x)/4))
I’m fairly new to Matlab and very unexperienced, where I’m having dificulty is plotting these functions against x, say x = [-24 24] and n=1:1:50 or until square waves appear. I gained some experience plotting their partial sums using fplot, but that approach does not appear to work here. It isn’t feasible to plot the 50th partial sum. I’ve seen more arrayfun usage online, but I do not understand it whatsoever.
Any help and explanation would be greatly appreciated. Thanks in advance. arrays, function, time series MATLAB Answers — New Questions

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