[Tutorialsplanet.NET] Udemy - Signal processing problems, solved in MATLAB and in Python

•  3. Spectral and rhythmicity analyses/3. Fourier transform for spectral analyses.mp4  173.98 MB
•  10. Feature detection/6. Application Detect muscle movements from EMG recordings.mp4  151.47 MB
•  7. Wavelet analysis/8. MATLAB Time-frequency analysis with complex wavelets.mp4  140.35 MB
•  7. Wavelet analysis/5. Wavelet convolution for narrowband filtering.mp4  135.88 MB
•  10. Feature detection/4. Wavelet convolution for feature extraction.mp4  135.76 MB
•  11. Variability/3. Signal-to-noise ratio (SNR).mp4  132.79 MB
•  10. Feature detection/7. Full width at half-maximum.mp4  131.28 MB
•  10. Feature detection/2. Local maxima and minima.mp4  126.65 MB
•  8. Resampling, interpolating, extrapolating/9. Dynamic time warping.mp4  122.58 MB
•  3. Spectral and rhythmicity analyses/4. Welch's method and windowing.mp4  121.88 MB
•  5. Filtering/3. FIR filters with firls.mp4  119.83 MB
•  3. Spectral and rhythmicity analyses/2. Crash course on the Fourier transform.mp4  116.86 MB
•  5. Filtering/2. Filtering Intuition, goals, and types.mp4  115.25 MB
•  11. Variability/5. Entropy.mp4  112.3 MB
•  8. Resampling, interpolating, extrapolating/3. Downsampling.mp4  110.76 MB
•  2. Time series denoising/8. Remove nonlinear trend with polynomials.mp4  109.31 MB
•  10. Feature detection/3. Recover signal from noise amplitude.mp4  104.34 MB
•  8. Resampling, interpolating, extrapolating/2. Upsampling.mp4  100.91 MB
•  6. Convolution/3. Convolution in MATLAB.mp4  100.74 MB
•  5. Filtering/7. Avoid edge effects with reflection.mp4  99.3 MB
•  2. Time series denoising/3. Gaussian-smooth a time series.mp4  96.15 MB
•  8. Resampling, interpolating, extrapolating/6. Resample irregularly sampled data.mp4  93.92 MB
•  7. Wavelet analysis/2. What are wavelets.mp4  93.01 MB
•  10. Feature detection/5. Area under the curve.mp4  91.16 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  87.65 MB
•  5. Filtering/14. Quantifying roll-off characteristics.mp4  87.08 MB
•  2. Time series denoising/10. Remove artifact via least-squares template-matching.mp4  84.98 MB
•  5. Filtering/6. Causal and zero-phase-shift filters.mp4  82.47 MB
•  5. Filtering/5. IIR Butterworth filters.mp4  80.32 MB
•  9. Outlier detection/3. Outliers via local threshold exceedance.mp4  77.34 MB
•  8. Resampling, interpolating, extrapolating/8. Spectral interpolation.mp4  77.28 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  76.15 MB
•  11. Variability/2. Total and windowed variance and RMS.mp4  75.57 MB
•  5. Filtering/16. Use filtering to separate birds in a recording.mp4  74.66 MB
•  6. Convolution/2. Time-domain convolution.mp4  71.11 MB
•  9. Outlier detection/2. Outliers via standard deviation threshold.mp4  69.63 MB
•  6. Convolution/5. The convolution theorem.mp4  68.76 MB
•  2. Time series denoising/2. Mean-smooth a time series.mp4  66.16 MB
•  5. Filtering/8. Data length and filter kernel length.mp4  65.02 MB
•  5. Filtering/9. Low-pass filters.mp4  64.01 MB
•  7. Wavelet analysis/9. Time-frequency analysis of brain signals.mp4  63.48 MB
•  2. Time series denoising/5. Denoising EMG signals via TKEO.mp4  57.17 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  55.24 MB
•  8. Resampling, interpolating, extrapolating/5. Interpolation.mp4  55.2 MB
•  1. Introductions/5. Writing code vs. using toolboxesprograms.mp4  53.11 MB
•  5. Filtering/11. High-pass filters.mp4  52.42 MB