| 1. Introductions | |||
| 1. Signal processing = decision-making + tools.mp4 | 33.2 MB | ||
| 1. Signal processing = decision-making + tools.vtt | 5.09 KB | ||
| 2. Using MATLAB in this course.mp4 | 24.34 MB | ||
| 2. Using MATLAB in this course.vtt | 4.6 KB | ||
| 3. Using Octave-online in this course.mp4 | 33.55 MB | ||
| 3. Using Octave-online in this course.vtt | 6.3 KB | ||
| 4. Using Python in this course.mp4 | 23.7 MB | ||
| 4. Using Python in this course.vtt | 4.38 KB | ||
| 5. Writing code vs. using toolboxesprograms.mp4 | 53.11 MB | ||
| 5. Writing code vs. using toolboxesprograms.vtt | 8.45 KB | ||
| 6. Using the Q&A forum.mp4 | 26.82 MB | ||
| 6. Using the Q&A forum.vtt | 6.36 KB | ||
| 10. Feature detection | |||
| 1. MATLAB and Python code for this section.html | 73 B | ||
| 1.1 sigprocMXC_featuredet.zip.zip | 1.73 MB | ||
| 2. Local maxima and minima.mp4 | 126.65 MB | ||
| 2. Local maxima and minima.vtt | 18.66 KB | ||
| 3. Recover signal from noise amplitude.mp4 | 104.34 MB | ||
| 3. Recover signal from noise amplitude.vtt | 14.72 KB | ||
| 4. Wavelet convolution for feature extraction.mp4 | 135.76 MB | ||
| 4. Wavelet convolution for feature extraction.vtt | 17.26 KB | ||
| 5. Area under the curve.mp4 | 91.16 MB | ||
| 5. Area under the curve.vtt | 15.25 KB | ||
| 6. Application Detect muscle movements from EMG recordings.mp4 | 151.47 MB | ||
| 6. Application Detect muscle movements from EMG recordings.vtt | 21.38 KB | ||
| 7. Full width at half-maximum.mp4 | 131.28 MB | ||
| 7. Full width at half-maximum.vtt | 21.48 KB | ||
| 8. Code challenge find the features!.mp4 | 24.01 MB | ||
| 8. Code challenge find the features!.vtt | 4.06 KB | ||
| 11. Variability | |||
| 1. MATLAB and Python code for this section.html | 47 B | ||
| 1.1 sigprocMXC_variability.zip.zip | 22.16 MB | ||
| 2. Total and windowed variance and RMS.mp4 | 75.57 MB | ||
| 2. Total and windowed variance and RMS.vtt | 12.95 KB | ||
| 3. Signal-to-noise ratio (SNR).mp4 | 132.79 MB | ||
| 3. Signal-to-noise ratio (SNR).vtt | 17.85 KB | ||
| 4. Coefficient of variation (CV).mp4 | 28.8 MB | ||
| 4. Coefficient of variation (CV).vtt | 6.08 KB | ||
| 5. Entropy.mp4 | 112.3 MB | ||
| 5. Entropy.vtt | 19.75 KB | ||
| 6. Code challenge.mp4 | 23.53 MB | ||
| 6. Code challenge.vtt | 3.7 KB | ||
| 12. Discounts on related courses | |||
| 1. Join the community!.html | 553 B | ||
| 2. Bonus Coupons for related courses.html | 2.53 KB | ||
| 2. Time series denoising | |||
| 1. MATLAB and Python code for this section.html | 84 B | ||
| 1.1 sigprocMXC_TimeSeriesDenoising.zip.zip | 11.78 MB | ||
| 10. Remove artifact via least-squares template-matching.mp4 | 84.98 MB | ||
| 10. Remove artifact via least-squares template-matching.vtt | 12.34 KB | ||
| 11. Code challenge Denoise these signals!.mp4 | 7.5 MB | ||
| 11. Code challenge Denoise these signals!.vtt | 1.32 KB | ||
| 2. Mean-smooth a time series.mp4 | 66.16 MB | ||
| 2. Mean-smooth a time series.vtt | 10.21 KB | ||
| 3. Gaussian-smooth a time series.mp4 | 96.15 MB | ||
| 3. Gaussian-smooth a time series.vtt | 16.44 KB | ||
| 4. Gaussian-smooth a spike time series.mp4 | 42.2 MB | ||
| 4. Gaussian-smooth a spike time series.vtt | 6.43 KB | ||
| 5. Denoising EMG signals via TKEO.mp4 | 57.17 MB | ||
| 5. Denoising EMG signals via TKEO.vtt | 9.73 KB | ||
| 6. Median filter to remove spike noise.mp4 | 77.1 MB | ||
| 6. Median filter to remove spike noise.vtt | 12.23 KB | ||
| 7. Remove linear trend (detrending).mp4 | 12.85 MB | ||
| 7. Remove linear trend (detrending).vtt | 2.62 KB | ||
| 8. Remove nonlinear trend with polynomials.mp4 | 109.31 MB | ||
| 8. Remove nonlinear trend with polynomials.vtt | 18.17 KB | ||
| 9. Averaging multiple repetitions (time-synchronous averaging).mp4 | 49.75 MB | ||
| 9. Averaging multiple repetitions (time-synchronous averaging).vtt | 6.48 KB | ||
| 3. Spectral and rhythmicity analyses | |||
| 1. MATLAB and Python code for this section.html | 99 B | ||
| 1.1 sigprocMXC_spectral.zip.zip | 2.29 MB | ||
| 2. Crash course on the Fourier transform.mp4 | 116.86 MB | ||
| 2. Crash course on the Fourier transform.vtt | 18.65 KB | ||
| 3. Fourier transform for spectral analyses.mp4 | 173.98 MB | ||
| 3. Fourier transform for spectral analyses.vtt | 22.96 KB | ||
| 4. Welch's method and windowing.mp4 | 121.88 MB | ||
| 4. Welch's method and windowing.vtt | 18.48 KB | ||
| 5. Spectrogram of birdsong.mp4 | 76.15 MB | ||
| 5. Spectrogram of birdsong.vtt | 9.6 KB | ||
| 6. Code challenge Compute a spectrogram!.mp4 | 15.22 MB | ||
| 6. Code challenge Compute a spectrogram!.vtt | 3.14 KB | ||
| 4. Working with complex numbers | |||
| 1. MATLAB and Python code for this section.html | 46 B | ||
| 1.1 sigprocMXC_complex.zip.zip | 38.08 KB | ||
| 2. From the number line to the complex number plane.mp4 | 55.24 MB | ||
| 2. From the number line to the complex number plane.vtt | 12.42 KB | ||
| 3. Addition and subtraction with complex numbers.mp4 | 19.89 MB | ||
| 3. Addition and subtraction with complex numbers.vtt | 4.46 KB | ||
| 4. Multiplication with complex numbers.mp4 | 38.96 MB | ||
| 4. Multiplication with complex numbers.vtt | 7.97 KB | ||
| 5. The complex conjugate.mp4 | 23.08 MB | ||
| 5. The complex conjugate.vtt | 5.35 KB | ||
| 6. Division with complex numbers.mp4 | 18.76 MB | ||
| 6. Division with complex numbers.vtt | 4.49 KB | ||
| 7. Magnitude and phase of complex numbers.mp4 | 48.31 MB | ||
| 7. Magnitude and phase of complex numbers.vtt | 9.4 KB | ||
| 5. Filtering | |||
| 1. MATLAB and Python code for this section.html | 85 B | ||
| 1.1 sigprocMXC_filtering.zip.zip | 4.63 MB | ||
| 10. Windowed-sinc filters.mp4 | 87.7 MB | ||
| 10. Windowed-sinc filters.vtt | 14.23 KB | ||
| 11. High-pass filters.mp4 | 52.42 MB | ||
| 11. High-pass filters.vtt | 7.15 KB | ||
| 12. Narrow-band filters.mp4 | 55.9 MB | ||
| 12. Narrow-band filters.vtt | 7.92 KB | ||
| 13. Two-stage wide-band filter.mp4 | 42.23 MB | ||
| 13. Two-stage wide-band filter.vtt | 5.43 KB | ||
| 14. Quantifying roll-off characteristics.mp4 | 87.08 MB | ||
| 14. Quantifying roll-off characteristics.vtt | 13.29 KB | ||
| 15. Remove electrical line noise and its harmonics.mp4 | 91.1 MB | ||
| 15. Remove electrical line noise and its harmonics.vtt | 12.05 KB | ||
| 16. Use filtering to separate birds in a recording.mp4 | 74.66 MB | ||
| 16. Use filtering to separate birds in a recording.vtt | 7.67 KB | ||
| 17. Code challenge Filter these signals!.mp4 | 11.33 MB | ||
| 17. Code challenge Filter these signals!.vtt | 1.54 KB | ||
| 2. Filtering Intuition, goals, and types.mp4 | 115.25 MB | ||
| 2. Filtering Intuition, goals, and types.vtt | 19.15 KB | ||
| 3. FIR filters with firls.mp4 | 119.83 MB | ||
| 3. FIR filters with firls.vtt | 17.72 KB | ||
| 4. FIR filters with fir1.mp4 | 47.24 MB | ||
| 4. FIR filters with fir1.vtt | 6.96 KB | ||
| 5. IIR Butterworth filters.mp4 | 80.32 MB | ||
| 5. IIR Butterworth filters.vtt | 12.39 KB | ||
| 6. Causal and zero-phase-shift filters.mp4 | 82.47 MB | ||
| 6. Causal and zero-phase-shift filters.vtt | 11.85 KB | ||
| 7. Avoid edge effects with reflection.mp4 | 99.3 MB | ||
| 7. Avoid edge effects with reflection.vtt | 13.97 KB | ||
| 8. Data length and filter kernel length.mp4 | 65.02 MB | ||
| 8. Data length and filter kernel length.vtt | 9.83 KB | ||
| 9. Low-pass filters.mp4 | 64.01 MB | ||
| 9. Low-pass filters.vtt | 8.86 KB | ||
| 6. Convolution | |||
| 1. MATLAB and Python code for this section.html | 72 B | ||
| 1.1 sigprocMXC_convolution.zip.zip | 250.11 KB | ||
| 10. Code challenge Create a frequency-domain mean-smoothing filter.mp4 | 16.85 MB | ||
| 10. Code challenge Create a frequency-domain mean-smoothing filter.vtt | 2.07 KB | ||
| 2. Time-domain convolution.mp4 | 71.11 MB | ||
| 2. Time-domain convolution.vtt | 14.74 KB | ||
| 3. Convolution in MATLAB.mp4 | 100.74 MB | ||
| 3. Convolution in MATLAB.vtt | 15.6 KB | ||
| 4. Why is the kernel flipped backwards!!!.mp4 | 22.55 MB | ||
| 4. Why is the kernel flipped backwards!!!.vtt | 5.77 KB | ||
| 5. The convolution theorem.mp4 | 68.76 MB | ||
| 5. The convolution theorem.vtt | 11.96 KB | ||
| 6. Thinking about convolution as spectral multiplication.mp4 | 87.65 MB | ||
| 6. Thinking about convolution as spectral multiplication.vtt | 15.25 KB | ||
| 6.1 TFtheory.mp4.mp4 | 18.18 MB | ||
| 7. Convolution with time-domain Gaussian (smoothing filter).mp4 | 49.48 MB | ||
| 7. Convolution with time-domain Gaussian (smoothing filter).vtt | 7.27 KB | ||
| 8. Convolution with frequency-domain Gaussian (narrowband filter).mp4 | 51.82 MB | ||
| 8. Convolution with frequency-domain Gaussian (narrowband filter).vtt | 8.11 KB | ||
| 9. Convolution with frequency-domain Planck taper (bandpass filter).mp4 | 46.06 MB | ||
| 9. Convolution with frequency-domain Planck taper (bandpass filter).vtt | 7.46 KB | ||
| 7. Wavelet analysis | |||
| 1. MATLAB and Python code for this section.html | 84 B | ||
| 1.1 sigprocMXC_wavelets.zip.zip | 769.67 KB | ||
| 10. Code challenge Compare wavelet convolution and FIR filter!.mp4 | 13.36 MB | ||
| 10. Code challenge Compare wavelet convolution and FIR filter!.vtt | 2.54 KB | ||
| 2. What are wavelets.mp4 | 93.01 MB | ||
| 2. What are wavelets.vtt | 17.38 KB | ||
| 3. Convolution with wavelets.mp4 | 48.17 MB | ||
| 3. Convolution with wavelets.vtt | 6.59 KB | ||
| 4. Scientific publication about defining Morlet wavelets.html | 465 B | ||
| 5. Wavelet convolution for narrowband filtering.mp4 | 135.88 MB | ||
| 5. Wavelet convolution for narrowband filtering.vtt | 17.37 KB | ||
| 6. Overview Time-frequency analysis with complex wavelets.mp4 | 48.65 MB | ||
| 6. Overview Time-frequency analysis with complex wavelets.vtt | 9.54 KB | ||
| 7. Link to youtube channel with 3 hours of relevant material.html | 621 B | ||
| 8. MATLAB Time-frequency analysis with complex wavelets.mp4 | 140.35 MB | ||
| 8. MATLAB Time-frequency analysis with complex wavelets.vtt | 17.75 KB | ||
| 9. Time-frequency analysis of brain signals.mp4 | 63.48 MB | ||
| 9. Time-frequency analysis of brain signals.vtt | 9.9 KB | ||
| 8. Resampling, interpolating, extrapolating | |||
| 1. MATLAB and Python code for this section.html | 67 B | ||
| 1.1 sigprocMXC_resampling.zip.zip | 411.17 KB | ||
| 10. Code challenge denoise and downsample this signal!.mp4 | 25.17 MB | ||
| 10. Code challenge denoise and downsample this signal!.vtt | 5.03 KB | ||
| 2. Upsampling.mp4 | 100.91 MB | ||
| 2. Upsampling.vtt | 15.79 KB | ||
| 3. Downsampling.mp4 | 110.76 MB | ||
| 3. Downsampling.vtt | 14.76 KB | ||
| 4. Strategies for multirate signals.mp4 | 44.17 MB | ||
| 4. Strategies for multirate signals.vtt | 7.96 KB | ||
| 5. Interpolation.mp4 | 55.2 MB | ||
| 5. Interpolation.vtt | 9.42 KB | ||
| 6. Resample irregularly sampled data.mp4 | 93.92 MB | ||
| 6. Resample irregularly sampled data.vtt | 13.22 KB | ||
| 7. Extrapolation.mp4 | 36.67 MB | ||
| 7. Extrapolation.vtt | 7.15 KB | ||
| 8. Spectral interpolation.mp4 | 77.28 MB | ||
| 8. Spectral interpolation.vtt | 12.46 KB | ||
| 9. Dynamic time warping.mp4 | 122.58 MB | ||
| 9. Dynamic time warping.vtt | 19.71 KB | ||
| 9. Outlier detection | |||
| 1. MATLAB and Python code for this section.html | 72 B | ||
| 1.1 sigprocMXC_outliers.zip.zip | 268.27 KB | ||
| 2. Outliers via standard deviation threshold.mp4 | 69.63 MB | ||
| 2. Outliers via standard deviation threshold.vtt | 11.51 KB | ||
| 3. Outliers via local threshold exceedance.mp4 | 77.34 MB | ||
| 3. Outliers via local threshold exceedance.vtt | 10.71 KB | ||
| 4. Outlier time windows via sliding RMS.mp4 | 46.09 MB | ||
| 4. Outlier time windows via sliding RMS.vtt | 7.1 KB | ||
| 5. Code challenge.mp4 | 39.06 MB | ||
| 5. Code challenge.vtt | 4.59 KB | ||
| [Tutorialsplanet.NET].url | 128 B |
Udemy - Signal Processing Problems, Solved In MATLAB And In Python [TP]
Applications-oriented instruction on signal processing and digital signal processing (DSP) using MATLAB and Python codes
For more Udemy Courses: https://tutorialsplanet.net
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