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

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Description
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

File list
  • [Tutorialsplanet.NET] Udemy - Signal processing problems, solved in MATLAB and in Python
  • 1. Introductions/1. Signal processing = decision-making + tools.mp4 33.2 MB
  • 1. Introductions/1. Signal processing = decision-making + tools.vtt 5.1 KB
  • 1. Introductions/2. Using MATLAB in this course.mp4 24.3 MB
  • 1. Introductions/2. Using MATLAB in this course.vtt 4.6 KB
  • 1. Introductions/3. Using Octave-online in this course.mp4 33.5 MB
  • 1. Introductions/3. Using Octave-online in this course.vtt 6.3 KB
  • 1. Introductions/4. Using Python in this course.mp4 23.7 MB
  • 1. Introductions/4. Using Python in this course.vtt 4.4 KB
  • 1. Introductions/5. Writing code vs. using toolboxesprograms.mp4 53.1 MB
  • 1. Introductions/5. Writing code vs. using toolboxesprograms.vtt 8.5 KB
  • 1. Introductions/6. Using the Q&A forum.mp4 26.8 MB
  • 1. Introductions/6. Using the Q&A forum.vtt 6.4 KB
  • 10. Feature detection/1. MATLAB and Python code for this section.html 73 B
  • 10. Feature detection/1.1 sigprocMXC_featuredet.zip.zip 1.7 MB
  • 10. Feature detection/2. Local maxima and minima.mp4 126.6 MB
  • 10. Feature detection/2. Local maxima and minima.vtt 18.7 KB
  • 10. Feature detection/3. Recover signal from noise amplitude.mp4 104.3 MB
  • 10. Feature detection/3. Recover signal from noise amplitude.vtt 14.7 KB
  • 10. Feature detection/4. Wavelet convolution for feature extraction.mp4 135.8 MB
  • 10. Feature detection/4. Wavelet convolution for feature extraction.vtt 17.3 KB
  • 10. Feature detection/5. Area under the curve.mp4 91.2 MB
  • 10. Feature detection/5. Area under the curve.vtt 15.3 KB
  • 10. Feature detection/6. Application Detect muscle movements from EMG recordings.mp4 151.5 MB
  • 10. Feature detection/6. Application Detect muscle movements from EMG recordings.vtt 21.4 KB
  • 10. Feature detection/7. Full width at half-maximum.mp4 131.3 MB
  • 10. Feature detection/7. Full width at half-maximum.vtt 21.5 KB
  • 10. Feature detection/8. Code challenge find the features!.mp4 24 MB
  • 10. Feature detection/8. Code challenge find the features!.vtt 4.1 KB
  • 11. Variability/1. MATLAB and Python code for this section.html 47 B
  • 11. Variability/1.1 sigprocMXC_variability.zip.zip 22.2 MB
  • 11. Variability/2. Total and windowed variance and RMS.mp4 75.6 MB
  • 11. Variability/2. Total and windowed variance and RMS.vtt 12.9 KB
  • 11. Variability/3. Signal-to-noise ratio (SNR).mp4 132.8 MB
  • 11. Variability/3. Signal-to-noise ratio (SNR).vtt 17.8 KB
  • 11. Variability/4. Coefficient of variation (CV).mp4 28.8 MB
  • 11. Variability/4. Coefficient of variation (CV).vtt 6.1 KB
  • 11. Variability/5. Entropy.mp4 112.3 MB
  • 11. Variability/5. Entropy.vtt 19.8 KB
  • 11. Variability/6. Code challenge.mp4 23.5 MB
  • 11. Variability/6. Code challenge.vtt 3.7 KB
  • 12. Discounts on related courses/1. Join the community!.html 553 B
  • 12. Discounts on related courses/2. Bonus Coupons for related courses.html 2.5 KB
  • 2. Time series denoising/1. MATLAB and Python code for this section.html 84 B
  • 2. Time series denoising/1.1 sigprocMXC_TimeSeriesDenoising.zip.zip 11.8 MB
  • 2. Time series denoising/10. Remove artifact via least-squares template-matching.mp4 85 MB
  • 2. Time series denoising/10. Remove artifact via least-squares template-matching.vtt 12.3 KB
  • 2. Time series denoising/11. Code challenge Denoise these signals!.mp4 7.5 MB
  • 2. Time series denoising/11. Code challenge Denoise these signals!.vtt 1.3 KB
  • 2. Time series denoising/2. Mean-smooth a time series.mp4 66.2 MB
  • 2. Time series denoising/2. Mean-smooth a time series.vtt 10.2 KB
  • 2. Time series denoising/3. Gaussian-smooth a time series.mp4 96.2 MB
  • 2. Time series denoising/3. Gaussian-smooth a time series.vtt 16.4 KB
  • 2. Time series denoising/4. Gaussian-smooth a spike time series.mp4 42.2 MB
  • 2. Time series denoising/4. Gaussian-smooth a spike time series.vtt 6.4 KB
  • 2. Time series denoising/5. Denoising EMG signals via TKEO.mp4 57.2 MB
  • 2. Time series denoising/5. Denoising EMG signals via TKEO.vtt 9.7 KB
  • 2. Time series denoising/6. Median filter to remove spike noise.mp4 77.1 MB
  • 2. Time series denoising/6. Median filter to remove spike noise.vtt 12.2 KB
  • 2. Time series denoising/7. Remove linear trend (detrending).mp4 12.9 MB
  • 2. Time series denoising/7. Remove linear trend (detrending).vtt 2.6 KB
  • 2. Time series denoising/8. Remove nonlinear trend with polynomials.mp4 109.3 MB
  • 2. Time series denoising/8. Remove nonlinear trend with polynomials.vtt 18.2 KB
  • 2. Time series denoising/9. Averaging multiple repetitions (time-synchronous averaging).mp4 49.7 MB
  • 2. Time series denoising/9. Averaging multiple repetitions (time-synchronous averaging).vtt 6.5 KB
  • 3. Spectral and rhythmicity analyses/1. MATLAB and Python code for this section.html 99 B
  • 3. Spectral and rhythmicity analyses/1.1 sigprocMXC_spectral.zip.zip 2.3 MB
  • 3. Spectral and rhythmicity analyses/2. Crash course on the Fourier transform.mp4 116.9 MB
  • 3. Spectral and rhythmicity analyses/2. Crash course on the Fourier transform.vtt 18.6 KB
  • 3. Spectral and rhythmicity analyses/3. Fourier transform for spectral analyses.mp4 174 MB
  • 3. Spectral and rhythmicity analyses/3. Fourier transform for spectral analyses.vtt 23 KB
  • 3. Spectral and rhythmicity analyses/4. Welch's method and windowing.mp4 121.9 MB
  • 3. Spectral and rhythmicity analyses/4. Welch's method and windowing.vtt 18.5 KB
  • 3. Spectral and rhythmicity analyses/5. Spectrogram of birdsong.mp4 76.1 MB
  • 3. Spectral and rhythmicity analyses/5. Spectrogram of birdsong.vtt 9.6 KB
  • 3. Spectral and rhythmicity analyses/6. Code challenge Compute a spectrogram!.mp4 15.2 MB
  • 3. Spectral and rhythmicity analyses/6. Code challenge Compute a spectrogram!.vtt 3.1 KB
  • 4. Working with complex numbers/1. MATLAB and Python code for this section.html 46 B
  • 4. Working with complex numbers/1.1 sigprocMXC_complex.zip.zip 38.1 KB
  • 4. Working with complex numbers/2. From the number line to the complex number plane.mp4 55.2 MB
  • 4. Working with complex numbers/2. From the number line to the complex number plane.vtt 12.4 KB
  • 4. Working with complex numbers/3. Addition and subtraction with complex numbers.mp4 19.9 MB
  • 4. Working with complex numbers/3. Addition and subtraction with complex numbers.vtt 4.5 KB
  • 4. Working with complex numbers/4. Multiplication with complex numbers.mp4 39 MB
  • 4. Working with complex numbers/4. Multiplication with complex numbers.vtt 8 KB
  • 4. Working with complex numbers/5. The complex conjugate.mp4 23.1 MB
  • 4. Working with complex numbers/5. The complex conjugate.vtt 5.4 KB
  • 4. Working with complex numbers/6. Division with complex numbers.mp4 18.8 MB
  • 4. Working with complex numbers/6. Division with complex numbers.vtt 4.5 KB
  • 4. Working with complex numbers/7. Magnitude and phase of complex numbers.mp4 48.3 MB
  • 4. Working with complex numbers/7. Magnitude and phase of complex numbers.vtt 9.4 KB
  • 5. Filtering/1. MATLAB and Python code for this section.html 85 B
  • 5. Filtering/1.1 sigprocMXC_filtering.zip.zip 4.6 MB
  • 5. Filtering/10. Windowed-sinc filters.mp4 87.7 MB
  • 5. Filtering/10. Windowed-sinc filters.vtt 14.2 KB
  • 5. Filtering/11. High-pass filters.mp4 52.4 MB
  • 5. Filtering/11. High-pass filters.vtt 7.2 KB
  • 5. Filtering/12. Narrow-band filters.mp4 55.9 MB
  • 5. Filtering/12. Narrow-band filters.vtt 7.9 KB
  • 5. Filtering/13. Two-stage wide-band filter.mp4 42.2 MB

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