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Udemy Signal processing problems solved in MATLAB and in Python

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Udemy Signal processing problems solved in MATLAB and in Python

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Files:

Get Bonus Downloads Here.url 182 bytes
001 Signal processing = decision-making + tools.mp4 29.2 MB
001 Signal processing = decision-making + tools_en.vtt 4.9 KB
002 Using MATLAB in this course.mp4 9.2 MB
002 Using MATLAB in this course_en.vtt 4.6 KB
003 Using Octave-online in this course.mp4 16.9 MB
003 Using Octave-online in this course_en.vtt 6.3 KB
004 Using Python in this course.mp4 10.6 MB
004 Using Python in this course_en.vtt 4.3 KB
005 Having fun with filtered Glass dance.mp4 48.4 MB
005 Having fun with filtered Glass dance_en.vtt 9.0 KB
006 Writing code vs. using toolboxesprograms.mp4 24.8 MB
006 Writing code vs. using toolboxesprograms_en.vtt 8.5 KB
007 Using Udemy like a pro.mp4 25.7 MB
007 Using Udemy like a pro_en.vtt 10.3 KB
glassDance.mat 3.3 MB
sigprocMXC_filterGlass.ipynb 4.0 KB
sigprocMXC_filterGlass.m 1.7 KB
001 MATLAB and Python code for this section.html 80 bytes
002 Mean-smooth a time series.mp4 57.0 MB
002 Mean-smooth a time series_en.vtt 9.9 KB
003 Gaussian-smooth a time series.mp4 45.5 MB
003 Gaussian-smooth a time series_en.vtt 15.9 KB
004 Gaussian-smooth a spike time series.mp4 18.0 MB
004 Gaussian-smooth a spike time series_en.vtt 6.3 KB
005 Denoising EMG signals via TKEO.mp4 47.7 MB
005 Denoising EMG signals via TKEO_en.vtt 9.7 KB
006 Median filter to remove spike noise.mp4 25.8 MB
006 Median filter to remove spike noise_en.vtt 12.0 KB
007 Remove linear trend (detrending).mp4 4.7 MB
007 Remove linear trend (detrending)_en.vtt 2.6 KB
008 Remove nonlinear trend with polynomials.mp4 53.5 MB
008 Remove nonlinear trend with polynomials_en.vtt 17.8 KB
009 Averaging multiple repetitions (time-synchronous averaging).mp4 23.2 MB
009 Averaging multiple repetitions (time-synchronous averaging)_en.vtt 6.3 KB
010 Remove artifact via least-squares template-matching.mp4 39.8 MB
010 Remove artifact via least-squares template-matching_en.vtt 12.0 KB
011 Code challenge Denoise these signals!.mp4 3.4 MB
011 Code challenge Denoise these signals!_en.vtt 1.3 KB
denoising_codeChallenge.mat 60.4 KB
emg4TKEO.mat 8.1 KB
eyedat.mat 3.8 MB
sigprocMXC_GauSmoothSpikes.m 1.3 KB
sigprocMXC_Gaussian_smooth.m 2.3 KB
sigprocMXC_TKEO.m 1.3 KB
sigprocMXC_averaging.m 1.3 KB
sigprocMXC_detrend.m 543 bytes
sigprocMXC_mean_smooth.m 1.4 KB
sigprocMXC_median_filter.m 1.2 KB
sigprocMXC_polynomialDetrend.m 2.5 KB
sigprocMXC_template_projection.m 1.3 KB
sigprocMXC_timeSeriesDenoising.ipynb 19.5 KB
templateProjection.mat 7.5 MB
001 MATLAB and Python code for this section.html 97 bytes
002 Crash course on the Fourier transform.mp4 54.6 MB
002 Crash course on the Fourier transform_en.vtt 18.3 KB
003 Fourier transform for spectral analyses.mp4 70.0 MB
003 Fourier transform for spectral analyses_en.vtt 22.4 KB
004 Welch's method and windowing.mp4 40.7 MB
004 Welch's method and windowing_en.vtt 18.0 KB
005 Spectrogram of birdsong.mp4 31.2 MB
005 Spectrogram of birdsong_en.vtt 9.4 KB
006 Code challenge Compute a spectrogram!.mp4 5.6 MB
006 Code challenge Compute a spectrogram!_en.vtt 3.1 KB
EEGrestingState.mat 335.8 KB
XC403881.mp3 244.3 KB
XC403881.wav 1.7 MB
sigprocMXC_FourierTransform.m 2.5 KB
sigprocMXC_SpectBirdcall.m 1.4 KB
sigprocMXC_Welch.m 2.0 KB
sigprocMXC_spectral.ipynb 348.7 KB
spectral_codeChallenge.mat 61.5 KB
001 MATLAB and Python code for this section.html 44 bytes
002 From the number line to the complex number plane.mp4 21.3 MB
002 From the number line to the complex number plane_en.vtt 12.1 KB
003 Addition and subtraction with complex numbers.mp4 7.5 MB
003 Addition and subtraction with complex numbers_en.vtt 4.2 KB
004 Multiplication with complex numbers.mp4 17.1 MB
004 Multiplication with complex numbers_en.vtt 7.8 KB
005 The complex conjugate.mp4 10.5 MB
005 The complex conjugate_en.vtt 5.1 KB
006 Division with complex numbers.mp4 7.3 MB
006 Division with complex numbers_en.vtt 4.6 KB
007 Magnitude and phase of complex numbers.mp4 21.3 MB
007 Magnitude and phase of complex numbers_en.vtt 9.4 KB
signprocMXC_complexNumbers.ipynb 53.3 KB
sigprocMXC_complexAddSub.m 572 bytes
sigprocMXC_complexConj.m 484 bytes
sigprocMXC_complexDivision.m 387 bytes
sigprocMXC_complexIntro.m 1010 bytes
sigprocMXC_complexMult.m 612 bytes
sigprocMXC_complexPolar.m 1.0 KB
001 MATLAB and Python code for this section.html 85 bytes
002 Filtering Intuition, goals, and types.mp4 87.9 MB
002 Filtering Intuition, goals, and types_en.vtt 18.8 KB
003 FIR filters with firls.mp4 49.7 MB
003 FIR filters with firls_en.vtt 17.7 KB
004 FIR filters with fir1.mp4 22.7 MB
004 FIR filters with fir1_en.vtt 6.8 KB
005 IIR Butterworth filters.mp4 34.3 MB
005 IIR Butterworth filters_en.vtt 12.2 KB
006 Causal and zero-phase-shift filters.mp4 33.7 MB
006 Causal and zero-phase-shift filters_en.vtt 11.6 KB
007 Avoid edge effects with reflection.mp4 85.3 MB
007 Avoid edge effects with reflection_en.vtt 13.7 KB
008 Data length and filter kernel length.mp4 22.6 MB
008 Data length and filter kernel length_en.vtt 9.8 KB
009 Low-pass filters.mp4 30.2 MB
009 Low-pass filters_en.vtt 8.6 KB
010 Windowed-sinc filters.mp4 37.1 MB
010 Windowed-sinc filters_en.vtt 13.9 KB
011 High-pass filters.mp4 21.6 MB
011 High-pass filters_en.vtt 6.9 KB
012 Narrow-band filters.mp4 23.3 MB
012 Narrow-band filters_en.vtt 7.8 KB
013 Two-stage wide-band filter.mp4 37.3 MB
013 Two-stage wide-band filter_en.vtt 5.5 KB
014 Quantifying roll-off characteristics.mp4 36.3 MB
014 Quantifying roll-off characteristics_en.vtt 13.0 KB
015 Remove electrical line noise and its harmonics.mp4 37.8 MB
015 Remove electrical line noise and its harmonics_en.vtt 12.5 KB
016 Use filtering to separate birds in a recording.mp4 35.4 MB
016 Use filtering to separate birds in a recording_en.vtt 7.6 KB
017 Code challenge Filter these signals!.mp4 5.0 MB
017 Code challenge Filter these signals!_en.vtt 1.7 KB
XC403881.mp3 244.3 KB
XC403881.wav 1.7 MB
filtering_codeChallenge.mat 150.5 KB
lineNoiseData.mat 2.2 MB
sigprocMXC_2stageWide.m 3.4 KB
sigprocMXC_butter.m 3.2 KB
sigprocMXC_causal0phase.m 1.7 KB
sigprocMXC_filterTheBirds.m 2.0 KB
sigprocMXC_filtering_part1.ipynb 1.4 MB
sigprocMXC_filtering_part2.ipynb 1.7 MB
sigprocMXC_fir1.m 2.6 KB
sigprocMXC_firls.m 3.6 KB
sigprocMXC_highpass.m 2.5 KB
sigprocMXC_linenoise.m 2.1 KB
sigprocMXC_lowpass.m 2.0 KB
sigprocMXC_narrowband.m 1.7 KB
sigprocMXC_reflection.m 2.3 KB
sigprocMXC_rolloff.m 2.3 KB
sigprocMXC_signalLength.m 709 bytes
sigprocMXC_windowSinc.m 3.1 KB
001 MATLAB and Python code for this section.html 70 bytes
002 Time-domain convolution.mp4 35.0 MB
002 Time-domain convolution_en.vtt 14.3 KB
003 Convolution in MATLAB.mp4 41.6 MB
003 Convolution in MATLAB_en.vtt 15.3 KB
004 Why is the kernel flipped backwards!!!.mp4 9.0 MB
004 Why is the kernel flipped backwards!!!_en.vtt 5.8 KB
005 The convolution theorem.mp4 29.3 MB
005 The convolution theorem_en.vtt 11.8 KB
006 Thinking about convolution as spectral multiplication.mp4 34.7 MB
006 Thinking about convolution as spectral multiplication_en.vtt 15.0 KB
007 Convolution with time-domain Gaussian (smoothing filter).mp4 21.0 MB
007 Convolution with time-domain Gaussian (smoothing filter)_en.vtt 7.1 KB
008 Convolution with frequency-domain Gaussian (narrowband filter).mp4 25.7 MB
008 Convolution with frequency-domain Gaussian (narrowband filter)_en.vtt 8.0 KB
009 Convolution with frequency-domain Planck taper (bandpass filter).mp4 22.2 MB
009 Convolution with frequency-domain Planck taper (bandpass filter)_en.vtt 7.2 KB
010 Code challenge Create a frequency-domain mean-smoothing filter.mp4 5.1 MB
010 Code challenge Create a frequency-domain mean-smoothing filter_en.vtt 2.1 KB
sigprocMXC_FreqDomainGaus.m 1.8 KB
sigprocMXC_TimeDomainGaus.m 2.3 KB
sigprocMXC_convolution.ipynb 352.6 KB
sigprocMXC_convolutionTheorem.m 1.5 KB
sigprocMXC_planckBandPass.m 2.3 KB
sigprocMXC_timeConvolution.m 2.9 KB
001 MATLAB and Python code for this section.html 84 bytes
002 What are wavelets.mp4 72.7 MB
002 What are wavelets_en.vtt 16.6 KB
003 Convolution with wavelets.mp4 22.8 MB
003 Convolution with wavelets_en.vtt 6.5 KB
004 Scientific publication about defining Morlet wavelets.html 465 bytes
005 Wavelet convolution for narrowband filtering.mp4 55.4 MB
005 Wavelet convolution for narrowband filtering_en.vtt 17.2 KB
006 Overview Time-frequency analysis with complex wavelets.mp4 20.6 MB
006 Overview Time-frequency analysis with complex wavelets_en.vtt 9.5 KB
007 Link to youtube channel with 3 hours of relevant material.html 621 bytes
008 MATLAB Time-frequency analysis with complex wavelets.mp4 113.6 MB
008 MATLAB Time-frequency analysis with complex wavelets_en.vtt 17.3 KB
009 Time-frequency analysis of brain signals.mp4 27.8 MB
009 Time-frequency analysis of brain signals_en.vtt 9.8 KB
010 Code challenge Compare wavelet convolution and FIR filter!.mp4 5.1 MB
010 Code challenge Compare wavelet convolution and FIR filter!_en.vtt 2.5 KB
data4TF.mat 17.1 KB
sigprocMXC_timefreq.m 2.2 KB
sigprocMXC_timefreqBrain.m 2.4 KB
sigprocMXC_wavelet.ipynb 21.6 KB
sigprocMXC_waveletConv.m 2.1 KB
sigprocMXC_waveletTF.m 3.4 KB
sigprocMXC_wavelets.m 3.3 KB
sigprocMXC_wavelets4narrowband.m 2.7 KB
wavelet_codeChallenge.mat 276.7 KB
001 MATLAB and Python code for this section.html 67 bytes
002 Upsampling.mp4 43.3 MB
002 Upsampling_en.vtt 15.5 KB
003 Downsampling.mp4 51.5 MB
003 Downsampling_en.vtt 14.4 KB
004 Strategies for multirate signals.mp4 38.4 MB
004 Strategies for multirate signals_en.vtt 7.9 KB
005 Interpolation.mp4 27.2 MB
005 Interpolation_en.vtt 9.3 KB
006 Resample irregularly sampled data.mp4 39.0 MB
006 Resample irregularly sampled data_en.vtt 13.2 KB
007 Extrapolation.mp4 18.4 MB
007 Extrapolation_en.vtt 7.1 KB
008 Spectral interpolation.mp4 26.2 MB
008 Spectral interpolation_en.vtt 12.0 KB
009 Dynamic time warping.mp4 50.3 MB
009 Dynamic time warping_en.vtt 19.1 KB
010 Code challenge denoise and downsample this signal!.mp4 9.5 MB
010 Code challenge denoise and downsample this signal!_en.vtt 5.1 KB
resample_codeChallenge.mat 52.2 KB
sigprocMXC_downsample.m 2.8 KB
sigprocMXC_dtw.m 1.6 KB
sigprocMXC_extrap.m 1.0 KB
sigprocMXC_interp.m 1.9 KB
sigprocMXC_irregular.m 1.8 KB
sigprocMXC_multirate.m 1.9 KB
sigprocMXC_resample.ipynb 19.9 KB
sigprocMXC_spectralInterp.m 1.2 KB
sigprocMXC_upsample.m 1.9 KB
001 MATLAB and Python code for this section.html 72 bytes
002 Outliers via standard deviation threshold.mp4 30.3 MB
002 Outliers via standard deviation threshold_en.vtt 11.3 KB
003 Outliers via local threshold exceedance.mp4 25.1 MB
003 Outliers via local threshold exceedance_en.vtt 10.4 KB
004 Outlier time windows via sliding RMS.mp4 16.0 MB
004 Outlier time windows via sliding RMS_en.vtt 6.9 KB
005 Code challenge.mp4 15.2 MB
005 Code challenge_en.vtt 4.5 KB
forex.mat 172.7 KB
sigprocMXC_RMSoutlierWindows.m 1.6 KB
sigprocMXC_localOutliers.m 1.8 KB
sigprocMXC_outZ.m 999 bytes
sigprocMXC_outliers.ipynb 129.2 KB
001 MATLAB and Python code for this section.html 71 bytes
002 Local maxima and minima.mp4 85.5 MB
002 Local maxima and minima_en.vtt 18.7 KB
003 Recover signal from noise amplitude.mp4 42.4 MB
003 Recover signal from noise amplitude_en.vtt 14.2 KB
004 Wavelet convolution for feature extraction.mp4 104.6 MB
004 Wavelet convolution for feature extraction_en.vtt 16.9 KB
005 Area under the curve.mp4 39.5 MB
005 Area under the curve_en.vtt 15.2 KB
006 Application Detect muscle movements from EMG recordings.mp4 64.0 MB
006 Application Detect muscle movements from EMG recordings_en.vtt 20.8 KB
007 Full width at half-maximum.mp4 64.8 MB
007 Full width at half-maximum_en.vtt 21.1 KB
008 Code challenge find the features!.mp4 10.7 MB
008 Code challenge find the features!_en.vtt 4.0 KB
EMGRT.mat 1.1 MB
sigprocMXC_AUC.m 1.3 KB
sigprocMXC_EMGonsets.m 2.3 KB
sigprocMXC_FWHM.m 3.0 KB
sigprocMXC_featuredetection.ipynb 22.5 KB
sigprocMXC_localMinMax.m 1.5 KB
sigprocMXC_signalFromNoise.m 2.4 KB
sigprocMXC_waveletFeatureEx.m 2.6 KB
001 MATLAB and Python code for this section.html 47 bytes
002 Total and windowed variance and RMS.mp4 26.5 MB
002 Total and windowed variance and RMS_en.vtt 12.9 KB
003 Signal-to-noise ratio (SNR).mp4 54.4 MB
003 Signal-to-noise ratio (SNR)_en.vtt 17.6 KB
004 Coefficient of variation (CV).mp4 10.5 MB
004 Coefficient of variation (CV)_en.vtt 6.0 KB
005 Entropy.mp4 55.9 MB
005 Entropy_en.vtt 19.2 KB
006 Code challenge.mp4 10.4 MB
006 Code challenge_en.vtt 3.7 KB
SNRdata.mat 4.5 MB
sigprocMXC_CV.m 779 bytes
sigprocMXC_SNR.m 2.7 KB
sigprocMXC_entropy.m 2.9 KB
sigprocMXC_variability.ipynb 13.0 KB
sigprocMXC_windowedVar.m 1.1 KB
v1_laminar.mat 17.4 MB
001 Bonus lecture.html 3.8 KB
Bonus Resources.txt 386 bytes

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