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

Torrent Hash :
bc3627211cf1f917d23212dfba28ae2cbc190a17
Content Size :
5.7 GB
Date :
2019-11-20
Short Magnet :
Short Magnet
https://0mag.me/!Rx9yJQ QR code
Files ( 194 )size
3. Spectral and rhythmicity analyses/3. Fourier transform for spectral analyses.mp4173.98 MB
10. Feature detection/6. Application Detect muscle movements from EMG recordings.mp4151.47 MB
7. Wavelet analysis/8. MATLAB Time-frequency analysis with complex wavelets.mp4140.35 MB
7. Wavelet analysis/5. Wavelet convolution for narrowband filtering.mp4135.88 MB
10. Feature detection/4. Wavelet convolution for feature extraction.mp4135.76 MB
11. Variability/3. Signal-to-noise ratio (SNR).mp4132.79 MB
10. Feature detection/7. Full width at half-maximum.mp4131.28 MB
10. Feature detection/2. Local maxima and minima.mp4126.65 MB
8. Resampling, interpolating, extrapolating/9. Dynamic time warping.mp4122.58 MB
3. Spectral and rhythmicity analyses/4. Welch's method and windowing.mp4121.88 MB
5. Filtering/3. FIR filters with firls.mp4119.83 MB
3. Spectral and rhythmicity analyses/2. Crash course on the Fourier transform.mp4116.86 MB
5. Filtering/2. Filtering Intuition, goals, and types.mp4115.25 MB
11. Variability/5. Entropy.mp4112.3 MB
8. Resampling, interpolating, extrapolating/3. Downsampling.mp4110.76 MB
2. Time series denoising/8. Remove nonlinear trend with polynomials.mp4109.31 MB
10. Feature detection/3. Recover signal from noise amplitude.mp4104.34 MB
8. Resampling, interpolating, extrapolating/2. Upsampling.mp4100.91 MB
6. Convolution/3. Convolution in MATLAB.mp4100.74 MB
5. Filtering/7. Avoid edge effects with reflection.mp499.3 MB
2. Time series denoising/3. Gaussian-smooth a time series.mp496.15 MB
8. Resampling, interpolating, extrapolating/6. Resample irregularly sampled data.mp493.92 MB
7. Wavelet analysis/2. What are wavelets.mp493.01 MB
10. Feature detection/5. Area under the curve.mp491.16 MB
5. Filtering/15. Remove electrical line noise and its harmonics.mp491.1 MB
5. Filtering/10. Windowed-sinc filters.mp487.7 MB
6. Convolution/6. Thinking about convolution as spectral multiplication.mp487.65 MB
5. Filtering/14. Quantifying roll-off characteristics.mp487.08 MB
2. Time series denoising/10. Remove artifact via least-squares template-matching.mp484.98 MB
5. Filtering/6. Causal and zero-phase-shift filters.mp482.47 MB
5. Filtering/5. IIR Butterworth filters.mp480.32 MB
9. Outlier detection/3. Outliers via local threshold exceedance.mp477.34 MB
8. Resampling, interpolating, extrapolating/8. Spectral interpolation.mp477.28 MB
2. Time series denoising/6. Median filter to remove spike noise.mp477.1 MB
3. Spectral and rhythmicity analyses/5. Spectrogram of birdsong.mp476.15 MB
11. Variability/2. Total and windowed variance and RMS.mp475.57 MB
5. Filtering/16. Use filtering to separate birds in a recording.mp474.66 MB
6. Convolution/2. Time-domain convolution.mp471.11 MB
9. Outlier detection/2. Outliers via standard deviation threshold.mp469.63 MB
6. Convolution/5. The convolution theorem.mp468.76 MB
2. Time series denoising/2. Mean-smooth a time series.mp466.16 MB
5. Filtering/8. Data length and filter kernel length.mp465.02 MB
5. Filtering/9. Low-pass filters.mp464.01 MB
7. Wavelet analysis/9. Time-frequency analysis of brain signals.mp463.48 MB
2. Time series denoising/5. Denoising EMG signals via TKEO.mp457.17 MB
5. Filtering/12. Narrow-band filters.mp455.9 MB
4. Working with complex numbers/2. From the number line to the complex number plane.mp455.24 MB
8. Resampling, interpolating, extrapolating/5. Interpolation.mp455.2 MB
1. Introductions/5. Writing code vs. using toolboxesprograms.mp453.11 MB
5. Filtering/11. High-pass filters.mp452.42 MB

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