Does anyone has WaveformData data referred in the "Time Series Anomaly Detection Using Deep Learning" example?
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This is the data I'm referring to:
https://in.mathworks.com/help/deeplearning/ug/time-series-anomaly-detection-using-deep-learning.html
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Maria Battle
am 21 Okt. 2022
Bearbeitet: Maria Battle
am 1 Nov. 2022
If for some reason you don't have access to WaveformData, you might be able to create a dataset for yourself using a wave form generator. It's not necessarily elegant, but the below might get you started. Ref: https://www.mathworks.com/help/wlan/gs/waveform-generation.html
wave_out = cell(1);
for k = 1:5 % specify how many samples you want
cfgHESU = wlanHESUConfig;
bits = randi([0 1],1,4);
osf = 2;
waveformHESU = wlanWaveformGenerator(bits,cfgHESU, ...
NumPackets=1,IdleTime=15e-6, ...
OversamplingFactor=osf);
fsHESU = wlanSampleRate(cfgHESU.ChannelBandwidth);
time = (0:length(waveformHESU)-1)/fsHESU;
wave_out{k} = [time; abs(waveformHESU')];
end
1 Kommentar
S Baharath Sai
am 1 Nov. 2022
Nikolaev
am 3 Apr. 2024
0 Stimmen
wave_out = cell(1);
for k = 1:5 % specify how many samples you want
cfgHESU = wlanHESUConfig;
bits = randi([0 1],1,4);
osf = 2;
waveformHESU = wlanWaveformGenerator(bits,cfgHESU, ...
NumPackets=1,IdleTime=15e-6, ...
OversamplingFactor=osf);
fsHESU = wlanSampleRate(cfgHESU.ChannelBandwidth);
time = (0:length(waveformHESU)-1)/fsHESU;
wave_out{k} = [time; abs(waveformHESU')];
end
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