Gaussian Noise Error message

Please could you look into this Gaussian Noise Simulation Error. Attached also is the error

Answer 1

[Image Analyst]

The error seems clear. You're tying to use "signal" in a function where it does not exist. I didn't look at the code but nowhere did you either pass in "signal" or create it in the function. You need to do one or the other.

[DGM]

I'll add

% ...
sigEner = norm(signals(:))^2;                % energy of the signal
noiseEner = sigEner/(10^(reqSNR/10));        % energy of noise to be added
noiseVar = noiseEner/(length(signal(:))-1);     % variance of noise to be added
St = sqrt(noiseVar);                   % std. deviation of noise to be added
noise = St*randn(size(signal));        % noise
noisySig = signal+noise;               % noisy signal
% ...

There is a variable called signals which appears to suddenly change its name to signal

[john amoo otoo]

I tried adding s to signals to make it signals. My signals has been defined in the "Process Data" script

[Image Analyst]

Replacing "signal" with "signals" in getmswtfeat fixes the signal problem but you have an index out of range error. I trust you can figure that one out, right?

%% load the data first
load('John_3PhaseFault0ohm.mat')
%% does this signal has any NaNs, if so remove
SteadyStateNoneFaultState = rmmissing(SteadyStateNoneFaultState);
Data3Phase0hmsFaultData = rmmissing(Data3Phase0hmsFaultData);
SSTime = SteadyStateNoneFaultState.Time;
SSNFS = SteadyStateNoneFaultState.SteadyStateNoneFaultState;
DPTime = Data3Phase0hmsFaultData.Time;
DPFD = Data3Phase0hmsFaultData.Data3Phase0hmsFaultData;
%% Define the filtering and inspect 
n                                = 8; 		%% defines window length
w                                = [-ones(n,1); ones(n,1)];
SSNFS = filter(w, n, SSNFS);
DPFD = filter(w, n, DPFD);
%% Normalize signals
med_training                     = prctile(SSNFS,50);
iqr_training                     = iqr(SSNFS);
SSNFS                            = (SSNFS-med_training)./iqr_training;
med_fault                        = prctile(DPFD,50);
iqr_fault                        = iqr(DPFD);
DPFD                             = (DPFD-med_fault)./iqr_fault;
% Plot & Observe the data
subplot(2,1,1)
plot(DPTime, DPFD)
title('filtered Data3Phase0hmsFaultData')
subplot(2,1,2)
plot(SSTime, SSNFS)
title('filtered SteadyStateNoneFaultState')

%% Let's observe the FFT power spectrum for differences
feat_fault = getmswtfeat(DPFD,32,16,100000);

Index in position 2 exceeds array bounds. Index must not exceed 52.

Error in getmswtfeat (line 117)
prob = percentENER(:,st:en);%./repmat(sum(percentENER(:,st:en),2),1,longs(k)) + eps;

feat_Good = getmswtfeat(SSNFS,32,16,100000);

[john amoo otoo]

Actually the main problem figuring and fixing the index error? How do you do that?

[Image Analyst]

@john amoo otoo I'd start here:

Debugging in MATLAB | Doug's MATLAB Video Tutorials

I don't have the Wavelet Toolbox and it's not possible to debug just by running code here in Answers. So the only way is for you to learn how to debug and debug it yourself. It's a skill you will need to learn eventually anyway. "Debugging via Answers" and waiting to see if someone who has the Wavelet Toolbox is willing to do your debugging for you is very slow and not reliable. It will be much faster to do it yourself.

[john amoo otoo]

What I am trying ti get at is to de-noise the signal and extract the features with getfeat

[Image Analyst]

Yes, debugging will definitely allow you to do that. Did you learn how to debug yet from the tutorial I showed you? If not, why not?