Gaussian Noise Error message

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john amoo otoo 2022-11-24

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https://ww2.mathworks.cn/matlabcentral/answers/1861898-gaussian-noise-error-message

评论： Image Analyst 2022-11-27

采纳的回答： Image Analyst

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

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Image Analyst 2022-11-24

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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.

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Image Analyst 2022-11-27

在 MATLAB Online 中打开

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 2022-11-27

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

Image Analyst 2022-11-27

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?

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