Udemy - Signal processing problems, solved in MATLAB and in Python - 磁力狗

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Udemy - Signal processing problems, solved in MATLAB and in Python的二维码

文档列表

3. Spectral and rhythmicity analyses/3. Fourier transform for spectral analyses.mp4 182.4 MB
10. Feature detection/6. Application Detect muscle movements from EMG recordings.mp4 158.8 MB
7. Wavelet analysis/8. MATLAB Time-frequency analysis with complex wavelets.mp4 147.2 MB
7. Wavelet analysis/5. Wavelet convolution for narrowband filtering.mp4 142.5 MB
10. Feature detection/4. Wavelet convolution for feature extraction.mp4 142.4 MB
11. Variability/3. Signal-to-noise ratio (SNR).mp4 139.2 MB
10. Feature detection/7. Full width at half-maximum.mp4 137.7 MB
10. Feature detection/2. Local maxima and minima.mp4 132.8 MB
8. Resampling, interpolating, extrapolating/9. Dynamic time warping.mp4 128.5 MB
3. Spectral and rhythmicity analyses/4. Welch's method and windowing.mp4 127.8 MB
5. Filtering/3. FIR filters with firls.mp4 125.7 MB
3. Spectral and rhythmicity analyses/2. Crash course on the Fourier transform.mp4 122.5 MB
5. Filtering/2. Filtering Intuition, goals, and types.mp4 120.8 MB
11. Variability/5. Entropy.mp4 117.8 MB
8. Resampling, interpolating, extrapolating/3. Downsampling.mp4 116.1 MB
2. Time series denoising/8. Remove nonlinear trend with polynomials.mp4 114.6 MB
10. Feature detection/3. Recover signal from noise amplitude.mp4 109.4 MB
8. Resampling, interpolating, extrapolating/2. Upsampling.mp4 105.8 MB
6. Convolution/3. Convolution in MATLAB.mp4 105.6 MB
5. Filtering/7. Avoid edge effects with reflection.mp4 104.1 MB
2. Time series denoising/3. Gaussian-smooth a time series.mp4 100.8 MB
8. Resampling, interpolating, extrapolating/6. Resample irregularly sampled data.mp4 98.5 MB
7. Wavelet analysis/2. What are wavelets.mp4 97.5 MB
10. Feature detection/5. Area under the curve.mp4 95.6 MB
5. Filtering/15. Remove electrical line noise and its harmonics.mp4 95.5 MB
5. Filtering/10. Windowed-sinc filters.mp4 92.0 MB
6. Convolution/6. Thinking about convolution as spectral multiplication.mp4 91.9 MB
5. Filtering/14. Quantifying roll-off characteristics.mp4 91.3 MB
2. Time series denoising/10. Remove artifact via least-squares template-matching.mp4 89.1 MB
5. Filtering/6. Causal and zero-phase-shift filters.mp4 86.5 MB
5. Filtering/5. IIR Butterworth filters.mp4 84.2 MB
9. Outlier detection/3. Outliers via local threshold exceedance.mp4 81.1 MB
8. Resampling, interpolating, extrapolating/8. Spectral interpolation.mp4 81.0 MB
2. Time series denoising/6. Median filter to remove spike noise.mp4 80.8 MB
3. Spectral and rhythmicity analyses/5. Spectrogram of birdsong.mp4 79.8 MB
11. Variability/2. Total and windowed variance and RMS.mp4 79.2 MB
5. Filtering/16. Use filtering to separate birds in a recording.mp4 78.3 MB
6. Convolution/2. Time-domain convolution.mp4 74.6 MB
9. Outlier detection/2. Outliers via standard deviation threshold.mp4 73.0 MB
6. Convolution/5. The convolution theorem.mp4 72.1 MB
2. Time series denoising/2. Mean-smooth a time series.mp4 69.4 MB
5. Filtering/8. Data length and filter kernel length.mp4 68.2 MB
5. Filtering/9. Low-pass filters.mp4 67.1 MB
7. Wavelet analysis/9. Time-frequency analysis of brain signals.mp4 66.6 MB
2. Time series denoising/5. Denoising EMG signals via TKEO.mp4 60.0 MB
5. Filtering/12. Narrow-band filters.mp4 58.6 MB
4. Working with complex numbers/2. From the number line to the complex number plane.mp4 57.9 MB
8. Resampling, interpolating, extrapolating/5. Interpolation.mp4 57.9 MB
1. Introductions/5. Writing code vs. using toolboxesprograms.mp4 55.7 MB
5. Filtering/11. High-pass filters.mp4 55.0 MB
6. Convolution/8. Convolution with frequency-domain Gaussian (narrowband filter).mp4 54.3 MB
2. Time series denoising/9. Averaging multiple repetitions (time-synchronous averaging).mp4 52.2 MB
6. Convolution/7. Convolution with time-domain Gaussian (smoothing filter).mp4 51.9 MB
7. Wavelet analysis/6. Overview Time-frequency analysis with complex wavelets.mp4 51.0 MB
4. Working with complex numbers/7. Magnitude and phase of complex numbers.mp4 50.7 MB
7. Wavelet analysis/3. Convolution with wavelets.mp4 50.5 MB
5. Filtering/4. FIR filters with fir1.mp4 49.5 MB
9. Outlier detection/4. Outlier time windows via sliding RMS.mp4 48.3 MB
6. Convolution/9. Convolution with frequency-domain Planck taper (bandpass filter).mp4 48.3 MB
8. Resampling, interpolating, extrapolating/4. Strategies for multirate signals.mp4 46.3 MB
5. Filtering/13. Two-stage wide-band filter.mp4 44.3 MB
2. Time series denoising/4. Gaussian-smooth a spike time series.mp4 44.3 MB
9. Outlier detection/5. Code challenge.mp4 41.0 MB
4. Working with complex numbers/4. Multiplication with complex numbers.mp4 40.9 MB
8. Resampling, interpolating, extrapolating/7. Extrapolation.mp4 38.5 MB
1. Introductions/3. Using Octave-online in this course.mp4 35.2 MB
1. Introductions/1. Signal processing = decision-making + tools.mp4 34.8 MB
11. Variability/4. Coefficient of variation (CV).mp4 30.2 MB
1. Introductions/6. Using the Q&A forum.mp4 28.1 MB
8. Resampling, interpolating, extrapolating/10. Code challenge denoise and downsample this signal!.mp4 26.4 MB
1. Introductions/2. Using MATLAB in this course.mp4 25.5 MB
10. Feature detection/8. Code challenge find the features!.mp4 25.2 MB
1. Introductions/4. Using Python in this course.mp4 24.9 MB
11. Variability/6. Code challenge.mp4 24.7 MB
4. Working with complex numbers/5. The complex conjugate.mp4 24.2 MB
6. Convolution/4. Why is the kernel flipped backwards!!!.mp4 23.6 MB
11. Variability/1.1 sigprocMXC_variability.zip.zip 23.2 MB
4. Working with complex numbers/3. Addition and subtraction with complex numbers.mp4 20.9 MB
4. Working with complex numbers/6. Division with complex numbers.mp4 19.7 MB
6. Convolution/6.1 TFtheory.mp4.mp4 19.1 MB
6. Convolution/10. Code challenge Create a frequency-domain mean-smoothing filter.mp4 17.7 MB
3. Spectral and rhythmicity analyses/6. Code challenge Compute a spectrogram!.mp4 16.0 MB
7. Wavelet analysis/10. Code challenge Compare wavelet convolution and FIR filter!.mp4 14.0 MB
2. Time series denoising/7. Remove linear trend (detrending).mp4 13.5 MB
2. Time series denoising/1.1 sigprocMXC_TimeSeriesDenoising.zip.zip 12.3 MB
5. Filtering/17. Code challenge Filter these signals!.mp4 11.9 MB
2. Time series denoising/11. Code challenge Denoise these signals!.mp4 7.9 MB
5. Filtering/1.1 sigprocMXC_filtering.zip.zip 4.9 MB
3. Spectral and rhythmicity analyses/1.1 sigprocMXC_spectral.zip.zip 2.4 MB
10. Feature detection/1.1 sigprocMXC_featuredet.zip.zip 1.8 MB
7. Wavelet analysis/1.1 sigprocMXC_wavelets.zip.zip 788.1 kB
8. Resampling, interpolating, extrapolating/1.1 sigprocMXC_resampling.zip.zip 421.0 kB
9. Outlier detection/1.1 sigprocMXC_outliers.zip.zip 274.7 kB
6. Convolution/1.1 sigprocMXC_convolution.zip.zip 256.1 kB
4. Working with complex numbers/1.1 sigprocMXC_complex.zip.zip 39.0 kB
3. Spectral and rhythmicity analyses/3. Fourier transform for spectral analyses.vtt 23.5 kB
10. Feature detection/7. Full width at half-maximum.vtt 22.0 kB
10. Feature detection/6. Application Detect muscle movements from EMG recordings.vtt 21.9 kB
11. Variability/5. Entropy.vtt 20.2 kB
8. Resampling, interpolating, extrapolating/9. Dynamic time warping.vtt 20.2 kB
5. Filtering/2. Filtering Intuition, goals, and types.vtt 19.6 kB
10. Feature detection/2. Local maxima and minima.vtt 19.1 kB
3. Spectral and rhythmicity analyses/2. Crash course on the Fourier transform.vtt 19.1 kB
3. Spectral and rhythmicity analyses/4. Welch's method and windowing.vtt 18.9 kB
2. Time series denoising/8. Remove nonlinear trend with polynomials.vtt 18.6 kB
11. Variability/3. Signal-to-noise ratio (SNR).vtt 18.3 kB
7. Wavelet analysis/8. MATLAB Time-frequency analysis with complex wavelets.vtt 18.2 kB
5. Filtering/3. FIR filters with firls.vtt 18.1 kB
7. Wavelet analysis/2. What are wavelets.vtt 17.8 kB
7. Wavelet analysis/5. Wavelet convolution for narrowband filtering.vtt 17.8 kB
10. Feature detection/4. Wavelet convolution for feature extraction.vtt 17.7 kB
2. Time series denoising/3. Gaussian-smooth a time series.vtt 16.8 kB
8. Resampling, interpolating, extrapolating/2. Upsampling.vtt 16.2 kB
6. Convolution/3. Convolution in MATLAB.vtt 16.0 kB
10. Feature detection/5. Area under the curve.vtt 15.6 kB
6. Convolution/6. Thinking about convolution as spectral multiplication.vtt 15.6 kB
8. Resampling, interpolating, extrapolating/3. Downsampling.vtt 15.1 kB
6. Convolution/2. Time-domain convolution.vtt 15.1 kB
10. Feature detection/3. Recover signal from noise amplitude.vtt 15.1 kB
5. Filtering/10. Windowed-sinc filters.vtt 14.6 kB
5. Filtering/7. Avoid edge effects with reflection.vtt 14.3 kB
5. Filtering/14. Quantifying roll-off characteristics.vtt 13.6 kB
8. Resampling, interpolating, extrapolating/6. Resample irregularly sampled data.vtt 13.5 kB
11. Variability/2. Total and windowed variance and RMS.vtt 13.3 kB
8. Resampling, interpolating, extrapolating/8. Spectral interpolation.vtt 12.8 kB
4. Working with complex numbers/2. From the number line to the complex number plane.vtt 12.7 kB
5. Filtering/5. IIR Butterworth filters.vtt 12.7 kB
2. Time series denoising/10. Remove artifact via least-squares template-matching.vtt 12.6 kB
2. Time series denoising/6. Median filter to remove spike noise.vtt 12.5 kB
5. Filtering/15. Remove electrical line noise and its harmonics.vtt 12.3 kB
6. Convolution/5. The convolution theorem.vtt 12.2 kB
5. Filtering/6. Causal and zero-phase-shift filters.vtt 12.1 kB
9. Outlier detection/2. Outliers via standard deviation threshold.vtt 11.8 kB
9. Outlier detection/3. Outliers via local threshold exceedance.vtt 11.0 kB
2. Time series denoising/2. Mean-smooth a time series.vtt 10.5 kB
7. Wavelet analysis/9. Time-frequency analysis of brain signals.vtt 10.1 kB
5. Filtering/8. Data length and filter kernel length.vtt 10.1 kB
2. Time series denoising/5. Denoising EMG signals via TKEO.vtt 10.0 kB
3. Spectral and rhythmicity analyses/5. Spectrogram of birdsong.vtt 9.8 kB
7. Wavelet analysis/6. Overview Time-frequency analysis with complex wavelets.vtt 9.8 kB
8. Resampling, interpolating, extrapolating/5. Interpolation.vtt 9.6 kB
4. Working with complex numbers/7. Magnitude and phase of complex numbers.vtt 9.6 kB
5. Filtering/9. Low-pass filters.vtt 9.1 kB
1. Introductions/5. Writing code vs. using toolboxesprograms.vtt 8.7 kB
6. Convolution/8. Convolution with frequency-domain Gaussian (narrowband filter).vtt 8.3 kB
4. Working with complex numbers/4. Multiplication with complex numbers.vtt 8.2 kB
8. Resampling, interpolating, extrapolating/4. Strategies for multirate signals.vtt 8.2 kB
5. Filtering/12. Narrow-band filters.vtt 8.1 kB
5. Filtering/16. Use filtering to separate birds in a recording.vtt 7.9 kB
6. Convolution/9. Convolution with frequency-domain Planck taper (bandpass filter).vtt 7.6 kB
6. Convolution/7. Convolution with time-domain Gaussian (smoothing filter).vtt 7.4 kB
5. Filtering/11. High-pass filters.vtt 7.3 kB
8. Resampling, interpolating, extrapolating/7. Extrapolation.vtt 7.3 kB
9. Outlier detection/4. Outlier time windows via sliding RMS.vtt 7.3 kB
5. Filtering/4. FIR filters with fir1.vtt 7.1 kB
7. Wavelet analysis/3. Convolution with wavelets.vtt 6.8 kB
2. Time series denoising/9. Averaging multiple repetitions (time-synchronous averaging).vtt 6.6 kB
2. Time series denoising/4. Gaussian-smooth a spike time series.vtt 6.6 kB
1. Introductions/6. Using the Q&A forum.vtt 6.5 kB
1. Introductions/3. Using Octave-online in this course.vtt 6.5 kB
11. Variability/4. Coefficient of variation (CV).vtt 6.2 kB
6. Convolution/4. Why is the kernel flipped backwards!!!.vtt 5.9 kB
5. Filtering/13. Two-stage wide-band filter.vtt 5.6 kB
4. Working with complex numbers/5. The complex conjugate.vtt 5.5 kB
1. Introductions/1. Signal processing = decision-making + tools.vtt 5.2 kB
8. Resampling, interpolating, extrapolating/10. Code challenge denoise and downsample this signal!.vtt 5.2 kB
1. Introductions/2. Using MATLAB in this course.vtt 4.7 kB
9. Outlier detection/5. Code challenge.vtt 4.7 kB
4. Working with complex numbers/6. Division with complex numbers.vtt 4.6 kB
4. Working with complex numbers/3. Addition and subtraction with complex numbers.vtt 4.6 kB
1. Introductions/4. Using Python in this course.vtt 4.5 kB
10. Feature detection/8. Code challenge find the features!.vtt 4.2 kB
11. Variability/6. Code challenge.vtt 3.8 kB
3. Spectral and rhythmicity analyses/6. Code challenge Compute a spectrogram!.vtt 3.2 kB
2. Time series denoising/7. Remove linear trend (detrending).vtt 2.7 kB
7. Wavelet analysis/10. Code challenge Compare wavelet convolution and FIR filter!.vtt 2.6 kB
12. Discounts on related courses/2. Bonus Coupons for related courses.html 2.6 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 1.6 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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