Udemy - Signal processing problems, solved in MATLAB and in Python
File List
- 3. Spectral and rhythmicity analyses/3. Fourier transform for spectral analyses.mp4 174.0 MB
- 10. Feature detection/6. Application Detect muscle movements from EMG recordings.mp4 151.5 MB
- 7. Wavelet analysis/8. MATLAB Time-frequency analysis with complex wavelets.mp4 140.3 MB
- 7. Wavelet analysis/5. Wavelet convolution for narrowband filtering.mp4 135.9 MB
- 10. Feature detection/4. Wavelet convolution for feature extraction.mp4 135.8 MB
- 11. Variability/3. Signal-to-noise ratio (SNR).mp4 132.8 MB
- 10. Feature detection/7. Full width at half-maximum.mp4 131.3 MB
- 10. Feature detection/2. Local maxima and minima.mp4 126.6 MB
- 8. Resampling, interpolating, extrapolating/9. Dynamic time warping.mp4 122.6 MB
- 3. Spectral and rhythmicity analyses/4. Welch's method and windowing.mp4 121.9 MB
- 5. Filtering/3. FIR filters with firls.mp4 119.8 MB
- 3. Spectral and rhythmicity analyses/2. Crash course on the Fourier transform.mp4 116.9 MB
- 5. Filtering/2. Filtering Intuition, goals, and types.mp4 115.2 MB
- 11. Variability/5. Entropy.mp4 112.3 MB
- 8. Resampling, interpolating, extrapolating/3. Downsampling.mp4 110.8 MB
- 2. Time series denoising/8. Remove nonlinear trend with polynomials.mp4 109.3 MB
- 10. Feature detection/3. Recover signal from noise amplitude.mp4 104.3 MB
- 8. Resampling, interpolating, extrapolating/2. Upsampling.mp4 100.9 MB
- 6. Convolution/3. Convolution in MATLAB.mp4 100.7 MB
- 5. Filtering/7. Avoid edge effects with reflection.mp4 99.3 MB
- 2. Time series denoising/3. Gaussian-smooth a time series.mp4 96.2 MB
- 8. Resampling, interpolating, extrapolating/6. Resample irregularly sampled data.mp4 93.9 MB
- 7. Wavelet analysis/2. What are wavelets.mp4 93.0 MB
- 10. Feature detection/5. Area under the curve.mp4 91.2 MB
- 5. Filtering/15. Remove electrical line noise and its harmonics.mp4 91.1 MB
- 5. Filtering/10. Windowed-sinc filters.mp4 87.7 MB
- 6. Convolution/6. Thinking about convolution as spectral multiplication.mp4 87.6 MB
- 5. Filtering/14. Quantifying roll-off characteristics.mp4 87.1 MB
- 2. Time series denoising/10. Remove artifact via least-squares template-matching.mp4 85.0 MB
- 5. Filtering/6. Causal and zero-phase-shift filters.mp4 82.5 MB
- 5. Filtering/5. IIR Butterworth filters.mp4 80.3 MB
- 9. Outlier detection/3. Outliers via local threshold exceedance.mp4 77.3 MB
- 8. Resampling, interpolating, extrapolating/8. Spectral interpolation.mp4 77.3 MB
- 2. Time series denoising/6. Median filter to remove spike noise.mp4 77.1 MB
- 3. Spectral and rhythmicity analyses/5. Spectrogram of birdsong.mp4 76.1 MB
- 11. Variability/2. Total and windowed variance and RMS.mp4 75.6 MB
- 5. Filtering/16. Use filtering to separate birds in a recording.mp4 74.7 MB
- 6. Convolution/2. Time-domain convolution.mp4 71.1 MB
- 9. Outlier detection/2. Outliers via standard deviation threshold.mp4 69.6 MB
- 6. Convolution/5. The convolution theorem.mp4 68.8 MB
- 2. Time series denoising/2. Mean-smooth a time series.mp4 66.2 MB
- 5. Filtering/8. Data length and filter kernel length.mp4 65.0 MB
- 5. Filtering/9. Low-pass filters.mp4 64.0 MB
- 7. Wavelet analysis/9. Time-frequency analysis of brain signals.mp4 63.5 MB
- 2. Time series denoising/5. Denoising EMG signals via TKEO.mp4 57.2 MB
- 5. Filtering/12. Narrow-band filters.mp4 55.9 MB
- 4. Working with complex numbers/2. From the number line to the complex number plane.mp4 55.2 MB
- 8. Resampling, interpolating, extrapolating/5. Interpolation.mp4 55.2 MB
- 1. Introductions/5. Writing code vs. using toolboxesprograms.mp4 53.1 MB
- 5. Filtering/11. High-pass filters.mp4 52.4 MB
- 6. Convolution/8. Convolution with frequency-domain Gaussian (narrowband filter).mp4 51.8 MB
- 2. Time series denoising/9. Averaging multiple repetitions (time-synchronous averaging).mp4 49.7 MB
- 6. Convolution/7. Convolution with time-domain Gaussian (smoothing filter).mp4 49.5 MB
- 7. Wavelet analysis/6. Overview Time-frequency analysis with complex wavelets.mp4 48.7 MB
- 4. Working with complex numbers/7. Magnitude and phase of complex numbers.mp4 48.3 MB
- 7. Wavelet analysis/3. Convolution with wavelets.mp4 48.2 MB
- 5. Filtering/4. FIR filters with fir1.mp4 47.2 MB
- 9. Outlier detection/4. Outlier time windows via sliding RMS.mp4 46.1 MB
- 6. Convolution/9. Convolution with frequency-domain Planck taper (bandpass filter).mp4 46.1 MB
- 8. Resampling, interpolating, extrapolating/4. Strategies for multirate signals.mp4 44.2 MB
- 5. Filtering/13. Two-stage wide-band filter.mp4 42.2 MB
- 2. Time series denoising/4. Gaussian-smooth a spike time series.mp4 42.2 MB
- 9. Outlier detection/5. Code challenge.mp4 39.1 MB
- 4. Working with complex numbers/4. Multiplication with complex numbers.mp4 39.0 MB
- 8. Resampling, interpolating, extrapolating/7. Extrapolation.mp4 36.7 MB
- 1. Introductions/3. Using Octave-online in this course.mp4 33.5 MB
- 1. Introductions/1. Signal processing = decision-making + tools.mp4 33.2 MB
- 11. Variability/4. Coefficient of variation (CV).mp4 28.8 MB
- 1. Introductions/6. Using the Q&A forum.mp4 26.8 MB
- 8. Resampling, interpolating, extrapolating/10. Code challenge denoise and downsample this signal!.mp4 25.2 MB
- 1. Introductions/2. Using MATLAB in this course.mp4 24.3 MB
- 10. Feature detection/8. Code challenge find the features!.mp4 24.0 MB
- 1. Introductions/4. Using Python in this course.mp4 23.7 MB
- 11. Variability/6. Code challenge.mp4 23.5 MB
- 4. Working with complex numbers/5. The complex conjugate.mp4 23.1 MB
- 6. Convolution/4. Why is the kernel flipped backwards!!!.mp4 22.5 MB
- 11. Variability/1.1 sigprocMXC_variability.zip.zip 22.2 MB
- 4. Working with complex numbers/3. Addition and subtraction with complex numbers.mp4 19.9 MB
- 4. Working with complex numbers/6. Division with complex numbers.mp4 18.8 MB
- 6. Convolution/6.1 TFtheory.mp4.mp4 18.2 MB
- 6. Convolution/10. Code challenge Create a frequency-domain mean-smoothing filter.mp4 16.9 MB
- 3. Spectral and rhythmicity analyses/6. Code challenge Compute a spectrogram!.mp4 15.2 MB
- 7. Wavelet analysis/10. Code challenge Compare wavelet convolution and FIR filter!.mp4 13.4 MB
- 2. Time series denoising/7. Remove linear trend (detrending).mp4 12.9 MB
- 2. Time series denoising/1.1 sigprocMXC_TimeSeriesDenoising.zip.zip 11.8 MB
- 5. Filtering/17. Code challenge Filter these signals!.mp4 11.3 MB
- 2. Time series denoising/11. Code challenge Denoise these signals!.mp4 7.5 MB
- 5. Filtering/1.1 sigprocMXC_filtering.zip.zip 4.6 MB
- 3. Spectral and rhythmicity analyses/1.1 sigprocMXC_spectral.zip.zip 2.3 MB
- 10. Feature detection/1.1 sigprocMXC_featuredet.zip.zip 1.7 MB
- 7. Wavelet analysis/1.1 sigprocMXC_wavelets.zip.zip 769.7 KB
- 8. Resampling, interpolating, extrapolating/1.1 sigprocMXC_resampling.zip.zip 411.2 KB
- 9. Outlier detection/1.1 sigprocMXC_outliers.zip.zip 268.3 KB
- 6. Convolution/1.1 sigprocMXC_convolution.zip.zip 250.1 KB
- 4. Working with complex numbers/1.1 sigprocMXC_complex.zip.zip 38.1 KB
- 3. Spectral and rhythmicity analyses/3. Fourier transform for spectral analyses.vtt 23.0 KB
- 10. Feature detection/7. Full width at half-maximum.vtt 21.5 KB
- 10. Feature detection/6. Application Detect muscle movements from EMG recordings.vtt 21.4 KB
- 11. Variability/5. Entropy.vtt 19.8 KB
- 8. Resampling, interpolating, extrapolating/9. Dynamic time warping.vtt 19.7 KB
- 5. Filtering/2. Filtering Intuition, goals, and types.vtt 19.1 KB
- 10. Feature detection/2. Local maxima and minima.vtt 18.7 KB
- 3. Spectral and rhythmicity analyses/2. Crash course on the Fourier transform.vtt 18.6 KB
- 3. Spectral and rhythmicity analyses/4. Welch's method and windowing.vtt 18.5 KB
- 2. Time series denoising/8. Remove nonlinear trend with polynomials.vtt 18.2 KB
- 11. Variability/3. Signal-to-noise ratio (SNR).vtt 17.8 KB
- 7. Wavelet analysis/8. MATLAB Time-frequency analysis with complex wavelets.vtt 17.8 KB
- 5. Filtering/3. FIR filters with firls.vtt 17.7 KB
- 7. Wavelet analysis/2. What are wavelets.vtt 17.4 KB
- 7. Wavelet analysis/5. Wavelet convolution for narrowband filtering.vtt 17.4 KB
- 10. Feature detection/4. Wavelet convolution for feature extraction.vtt 17.3 KB
- 2. Time series denoising/3. Gaussian-smooth a time series.vtt 16.4 KB
- 8. Resampling, interpolating, extrapolating/2. Upsampling.vtt 15.8 KB
- 6. Convolution/3. Convolution in MATLAB.vtt 15.6 KB
- 10. Feature detection/5. Area under the curve.vtt 15.3 KB
- 6. Convolution/6. Thinking about convolution as spectral multiplication.vtt 15.2 KB
- 8. Resampling, interpolating, extrapolating/3. Downsampling.vtt 14.8 KB
- 6. Convolution/2. Time-domain convolution.vtt 14.7 KB
- 10. Feature detection/3. Recover signal from noise amplitude.vtt 14.7 KB
- 5. Filtering/10. Windowed-sinc filters.vtt 14.2 KB
- 5. Filtering/7. Avoid edge effects with reflection.vtt 14.0 KB
- 5. Filtering/14. Quantifying roll-off characteristics.vtt 13.3 KB
- 8. Resampling, interpolating, extrapolating/6. Resample irregularly sampled data.vtt 13.2 KB
- 11. Variability/2. Total and windowed variance and RMS.vtt 12.9 KB
- 8. Resampling, interpolating, extrapolating/8. Spectral interpolation.vtt 12.5 KB
- 4. Working with complex numbers/2. From the number line to the complex number plane.vtt 12.4 KB
- 5. Filtering/5. IIR Butterworth filters.vtt 12.4 KB
- 2. Time series denoising/10. Remove artifact via least-squares template-matching.vtt 12.3 KB
- 2. Time series denoising/6. Median filter to remove spike noise.vtt 12.2 KB
- 5. Filtering/15. Remove electrical line noise and its harmonics.vtt 12.0 KB
- 6. Convolution/5. The convolution theorem.vtt 12.0 KB
- 5. Filtering/6. Causal and zero-phase-shift filters.vtt 11.9 KB
- 9. Outlier detection/2. Outliers via standard deviation threshold.vtt 11.5 KB
- 9. Outlier detection/3. Outliers via local threshold exceedance.vtt 10.7 KB
- 2. Time series denoising/2. Mean-smooth a time series.vtt 10.2 KB
- 7. Wavelet analysis/9. Time-frequency analysis of brain signals.vtt 9.9 KB
- 5. Filtering/8. Data length and filter kernel length.vtt 9.8 KB
- 2. Time series denoising/5. Denoising EMG signals via TKEO.vtt 9.7 KB
- 3. Spectral and rhythmicity analyses/5. Spectrogram of birdsong.vtt 9.6 KB
- 7. Wavelet analysis/6. Overview Time-frequency analysis with complex wavelets.vtt 9.5 KB
- 8. Resampling, interpolating, extrapolating/5. Interpolation.vtt 9.4 KB
- 4. Working with complex numbers/7. Magnitude and phase of complex numbers.vtt 9.4 KB
- 5. Filtering/9. Low-pass filters.vtt 8.9 KB
- 1. Introductions/5. Writing code vs. using toolboxesprograms.vtt 8.5 KB
- 6. Convolution/8. Convolution with frequency-domain Gaussian (narrowband filter).vtt 8.1 KB
- 4. Working with complex numbers/4. Multiplication with complex numbers.vtt 8.0 KB
- 8. Resampling, interpolating, extrapolating/4. Strategies for multirate signals.vtt 8.0 KB
- 5. Filtering/12. Narrow-band filters.vtt 7.9 KB
- 5. Filtering/16. Use filtering to separate birds in a recording.vtt 7.7 KB
- 6. Convolution/9. Convolution with frequency-domain Planck taper (bandpass filter).vtt 7.5 KB
- 6. Convolution/7. Convolution with time-domain Gaussian (smoothing filter).vtt 7.3 KB
- 5. Filtering/11. High-pass filters.vtt 7.2 KB
- 8. Resampling, interpolating, extrapolating/7. Extrapolation.vtt 7.1 KB
- 9. Outlier detection/4. Outlier time windows via sliding RMS.vtt 7.1 KB
- 5. Filtering/4. FIR filters with fir1.vtt 7.0 KB
- 7. Wavelet analysis/3. Convolution with wavelets.vtt 6.6 KB
- 2. Time series denoising/9. Averaging multiple repetitions (time-synchronous averaging).vtt 6.5 KB
- 2. Time series denoising/4. Gaussian-smooth a spike time series.vtt 6.4 KB
- 1. Introductions/6. Using the Q&A forum.vtt 6.4 KB
- 1. Introductions/3. Using Octave-online in this course.vtt 6.3 KB
- 11. Variability/4. Coefficient of variation (CV).vtt 6.1 KB
- 6. Convolution/4. Why is the kernel flipped backwards!!!.vtt 5.8 KB
- 5. Filtering/13. Two-stage wide-band filter.vtt 5.4 KB
- 4. Working with complex numbers/5. The complex conjugate.vtt 5.4 KB
- 1. Introductions/1. Signal processing = decision-making + tools.vtt 5.1 KB
- 8. Resampling, interpolating, extrapolating/10. Code challenge denoise and downsample this signal!.vtt 5.0 KB
- 1. Introductions/2. Using MATLAB in this course.vtt 4.6 KB
- 9. Outlier detection/5. Code challenge.vtt 4.6 KB
- 4. Working with complex numbers/6. Division with complex numbers.vtt 4.5 KB
- 4. Working with complex numbers/3. Addition and subtraction with complex numbers.vtt 4.5 KB
- 1. Introductions/4. Using Python in this course.vtt 4.4 KB
- 10. Feature detection/8. Code challenge find the features!.vtt 4.1 KB
- 11. Variability/6. Code challenge.vtt 3.7 KB
- 3. Spectral and rhythmicity analyses/6. Code challenge Compute a spectrogram!.vtt 3.1 KB
- 2. Time series denoising/7. Remove linear trend (detrending).vtt 2.6 KB
- 7. Wavelet analysis/10. Code challenge Compare wavelet convolution and FIR filter!.vtt 2.5 KB
- 12. Discounts on related courses/2. Bonus Coupons for related courses.html 2.5 KB
- 6. Convolution/10. Code challenge Create a frequency-domain mean-smoothing filter.vtt 2.1 KB
- 5. Filtering/17. Code challenge Filter these signals!.vtt 1.5 KB
- 2. Time series denoising/11. Code challenge Denoise these signals!.vtt 1.3 KB
- 7. Wavelet analysis/7. Link to youtube channel with 3 hours of relevant material.html 621 bytes
- 12. Discounts on related courses/1. Join the community!.html 553 bytes
- 7. Wavelet analysis/4. Scientific publication about defining Morlet wavelets.html 465 bytes
- Visit Getnewcourses.com.url 343 bytes
- Visit Freecourseit.com.url 342 bytes
- 1. Introductions/ReadMe.txt 241 bytes
- ReadMe.txt 241 bytes
- 3. Spectral and rhythmicity analyses/1. MATLAB and Python code for this section.html 99 bytes
- 5. Filtering/1. MATLAB and Python code for this section.html 85 bytes
- 2. Time series denoising/1. MATLAB and Python code for this section.html 84 bytes
- 7. Wavelet analysis/1. MATLAB and Python code for this section.html 84 bytes
- 10. Feature detection/1. MATLAB and Python code for this section.html 73 bytes
- 6. Convolution/1. MATLAB and Python code for this section.html 72 bytes
- 9. Outlier detection/1. MATLAB and Python code for this section.html 72 bytes
- 8. Resampling, interpolating, extrapolating/1. MATLAB and Python code for this section.html 67 bytes
- 11. Variability/1. MATLAB and Python code for this section.html 47 bytes
- 4. Working with complex numbers/1. MATLAB and Python code for this section.html 46 bytes
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