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| 1.1 sigprocMXC_complex.zip.zip |
38.08Кб |
| 1.1 sigprocMXC_convolution.zip.zip |
250.11Кб |
| 1.1 sigprocMXC_featuredet.zip.zip |
1.73Мб |
| 1.1 sigprocMXC_filtering.zip.zip |
4.63Мб |
| 1.1 sigprocMXC_outliers.zip.zip |
268.27Кб |
| 1.1 sigprocMXC_resampling.zip.zip |
411.17Кб |
| 1.1 sigprocMXC_spectral.zip.zip |
2.29Мб |
| 1.1 sigprocMXC_TimeSeriesDenoising.zip.zip |
11.78Мб |
| 1.1 sigprocMXC_variability.zip.zip |
22.16Мб |
| 1.1 sigprocMXC_wavelets.zip.zip |
769.67Кб |
| 1. Join the community!.html |
553б |
| 1. MATLAB and Python code for this section.html |
73б |
| 1. MATLAB and Python code for this section.html |
47б |
| 1. MATLAB and Python code for this section.html |
84б |
| 1. MATLAB and Python code for this section.html |
99б |
| 1. MATLAB and Python code for this section.html |
46б |
| 1. MATLAB and Python code for this section.html |
85б |
| 1. MATLAB and Python code for this section.html |
72б |
| 1. MATLAB and Python code for this section.html |
84б |
| 1. MATLAB and Python code for this section.html |
67б |
| 1. MATLAB and Python code for this section.html |
72б |
| 1. Signal processing = decision-making + tools.mp4 |
33.20Мб |
| 1. Signal processing = decision-making + tools.vtt |
5.09Кб |
| 10. Code challenge Compare wavelet convolution and FIR filter!.mp4 |
13.36Мб |
| 10. Code challenge Compare wavelet convolution and FIR filter!.vtt |
2.54Кб |
| 10. Code challenge Create a frequency-domain mean-smoothing filter.mp4 |
16.85Мб |
| 10. Code challenge Create a frequency-domain mean-smoothing filter.vtt |
2.07Кб |
| 10. Code challenge denoise and downsample this signal!.mp4 |
25.17Мб |
| 10. Code challenge denoise and downsample this signal!.vtt |
5.03Кб |
| 10. Remove artifact via least-squares template-matching.mp4 |
84.98Мб |
| 10. Remove artifact via least-squares template-matching.vtt |
12.34Кб |
| 10. Windowed-sinc filters.mp4 |
87.70Мб |
| 10. Windowed-sinc filters.vtt |
14.23Кб |
| 11. Code challenge Denoise these signals!.mp4 |
7.50Мб |
| 11. Code challenge Denoise these signals!.vtt |
1.32Кб |
| 11. High-pass filters.mp4 |
52.42Мб |
| 11. High-pass filters.vtt |
7.15Кб |
| 12. Narrow-band filters.mp4 |
55.90Мб |
| 12. Narrow-band filters.vtt |
7.92Кб |
| 13. Two-stage wide-band filter.mp4 |
42.23Мб |
| 13. Two-stage wide-band filter.vtt |
5.43Кб |
| 14. Quantifying roll-off characteristics.mp4 |
87.08Мб |
| 14. Quantifying roll-off characteristics.vtt |
13.29Кб |
| 15. Remove electrical line noise and its harmonics.mp4 |
91.10Мб |
| 15. Remove electrical line noise and its harmonics.vtt |
12.05Кб |
| 16. Use filtering to separate birds in a recording.mp4 |
74.66Мб |
| 16. Use filtering to separate birds in a recording.vtt |
7.67Кб |
| 17. Code challenge Filter these signals!.mp4 |
11.33Мб |
| 17. Code challenge Filter these signals!.vtt |
1.54Кб |
| 2. Bonus Coupons for related courses.html |
2.53Кб |
| 2. Crash course on the Fourier transform.mp4 |
116.86Мб |
| 2. Crash course on the Fourier transform.vtt |
18.65Кб |
| 2. Filtering Intuition, goals, and types.mp4 |
115.25Мб |
| 2. Filtering Intuition, goals, and types.vtt |
19.15Кб |
| 2. From the number line to the complex number plane.mp4 |
55.24Мб |
| 2. From the number line to the complex number plane.vtt |
12.42Кб |
| 2. Local maxima and minima.mp4 |
126.65Мб |
| 2. Local maxima and minima.vtt |
18.66Кб |
| 2. Mean-smooth a time series.mp4 |
66.16Мб |
| 2. Mean-smooth a time series.vtt |
10.21Кб |
| 2. Outliers via standard deviation threshold.mp4 |
69.63Мб |
| 2. Outliers via standard deviation threshold.vtt |
11.51Кб |
| 2. Time-domain convolution.mp4 |
71.11Мб |
| 2. Time-domain convolution.vtt |
14.74Кб |
| 2. Total and windowed variance and RMS.mp4 |
75.57Мб |
| 2. Total and windowed variance and RMS.vtt |
12.95Кб |
| 2. Upsampling.mp4 |
100.91Мб |
| 2. Upsampling.vtt |
15.79Кб |
| 2. Using MATLAB in this course.mp4 |
24.34Мб |
| 2. Using MATLAB in this course.vtt |
4.60Кб |
| 2. What are wavelets.mp4 |
93.01Мб |
| 2. What are wavelets.vtt |
17.38Кб |
| 3. Addition and subtraction with complex numbers.mp4 |
19.89Мб |
| 3. Addition and subtraction with complex numbers.vtt |
4.46Кб |
| 3. Convolution in MATLAB.mp4 |
100.74Мб |
| 3. Convolution in MATLAB.vtt |
15.60Кб |
| 3. Convolution with wavelets.mp4 |
48.17Мб |
| 3. Convolution with wavelets.vtt |
6.59Кб |
| 3. Downsampling.mp4 |
110.76Мб |
| 3. Downsampling.vtt |
14.76Кб |
| 3. FIR filters with firls.mp4 |
119.83Мб |
| 3. FIR filters with firls.vtt |
17.72Кб |
| 3. Fourier transform for spectral analyses.mp4 |
173.98Мб |
| 3. Fourier transform for spectral analyses.vtt |
22.96Кб |
| 3. Gaussian-smooth a time series.mp4 |
96.15Мб |
| 3. Gaussian-smooth a time series.vtt |
16.44Кб |
| 3. Outliers via local threshold exceedance.mp4 |
77.34Мб |
| 3. Outliers via local threshold exceedance.vtt |
10.71Кб |
| 3. Recover signal from noise amplitude.mp4 |
104.34Мб |
| 3. Recover signal from noise amplitude.vtt |
14.72Кб |
| 3. Signal-to-noise ratio (SNR).mp4 |
132.79Мб |
| 3. Signal-to-noise ratio (SNR).vtt |
17.85Кб |
| 3. Using Octave-online in this course.mp4 |
33.55Мб |
| 3. Using Octave-online in this course.vtt |
6.30Кб |
| 4. Coefficient of variation (CV).mp4 |
28.80Мб |
| 4. Coefficient of variation (CV).vtt |
6.08Кб |
| 4. FIR filters with fir1.mp4 |
47.24Мб |
| 4. FIR filters with fir1.vtt |
6.96Кб |
| 4. Gaussian-smooth a spike time series.mp4 |
42.20Мб |
| 4. Gaussian-smooth a spike time series.vtt |
6.43Кб |
| 4. Multiplication with complex numbers.mp4 |
38.96Мб |
| 4. Multiplication with complex numbers.vtt |
7.97Кб |
| 4. Outlier time windows via sliding RMS.mp4 |
46.09Мб |
| 4. Outlier time windows via sliding RMS.vtt |
7.10Кб |
| 4. Scientific publication about defining Morlet wavelets.html |
465б |
| 4. Strategies for multirate signals.mp4 |
44.17Мб |
| 4. Strategies for multirate signals.vtt |
7.96Кб |
| 4. Using Python in this course.mp4 |
23.70Мб |
| 4. Using Python in this course.vtt |
4.38Кб |
| 4. Wavelet convolution for feature extraction.mp4 |
135.76Мб |
| 4. Wavelet convolution for feature extraction.vtt |
17.26Кб |
| 4. Welch's method and windowing.mp4 |
121.88Мб |
| 4. Welch's method and windowing.vtt |
18.48Кб |
| 4. Why is the kernel flipped backwards!!!.mp4 |
22.55Мб |
| 4. Why is the kernel flipped backwards!!!.vtt |
5.77Кб |
| 5. Area under the curve.mp4 |
91.16Мб |
| 5. Area under the curve.vtt |
15.25Кб |
| 5. Code challenge.mp4 |
39.06Мб |
| 5. Code challenge.vtt |
4.59Кб |
| 5. Denoising EMG signals via TKEO.mp4 |
57.17Мб |
| 5. Denoising EMG signals via TKEO.vtt |
9.73Кб |
| 5. Entropy.mp4 |
112.30Мб |
| 5. Entropy.vtt |
19.75Кб |
| 5. IIR Butterworth filters.mp4 |
80.32Мб |
| 5. IIR Butterworth filters.vtt |
12.39Кб |
| 5. Interpolation.mp4 |
55.20Мб |
| 5. Interpolation.vtt |
9.42Кб |
| 5. Spectrogram of birdsong.mp4 |
76.15Мб |
| 5. Spectrogram of birdsong.vtt |
9.60Кб |
| 5. The complex conjugate.mp4 |
23.08Мб |
| 5. The complex conjugate.vtt |
5.35Кб |
| 5. The convolution theorem.mp4 |
68.76Мб |
| 5. The convolution theorem.vtt |
11.96Кб |
| 5. Wavelet convolution for narrowband filtering.mp4 |
135.88Мб |
| 5. Wavelet convolution for narrowband filtering.vtt |
17.37Кб |
| 5. Writing code vs. using toolboxesprograms.mp4 |
53.11Мб |
| 5. Writing code vs. using toolboxesprograms.vtt |
8.45Кб |
| 6.1 TFtheory.mp4.mp4 |
18.18Мб |
| 6. Application Detect muscle movements from EMG recordings.mp4 |
151.47Мб |
| 6. Application Detect muscle movements from EMG recordings.vtt |
21.38Кб |
| 6. Causal and zero-phase-shift filters.mp4 |
82.47Мб |
| 6. Causal and zero-phase-shift filters.vtt |
11.85Кб |
| 6. Code challenge.mp4 |
23.53Мб |
| 6. Code challenge.vtt |
3.70Кб |
| 6. Code challenge Compute a spectrogram!.mp4 |
15.22Мб |
| 6. Code challenge Compute a spectrogram!.vtt |
3.14Кб |
| 6. Division with complex numbers.mp4 |
18.76Мб |
| 6. Division with complex numbers.vtt |
4.49Кб |
| 6. Median filter to remove spike noise.mp4 |
77.10Мб |
| 6. Median filter to remove spike noise.vtt |
12.23Кб |
| 6. Overview Time-frequency analysis with complex wavelets.mp4 |
48.65Мб |
| 6. Overview Time-frequency analysis with complex wavelets.vtt |
9.54Кб |
| 6. Resample irregularly sampled data.mp4 |
93.92Мб |
| 6. Resample irregularly sampled data.vtt |
13.22Кб |
| 6. Thinking about convolution as spectral multiplication.mp4 |
87.65Мб |
| 6. Thinking about convolution as spectral multiplication.vtt |
15.25Кб |
| 6. Using the Q&A forum.mp4 |
26.82Мб |
| 6. Using the Q&A forum.vtt |
6.36Кб |
| 7. Avoid edge effects with reflection.mp4 |
99.30Мб |
| 7. Avoid edge effects with reflection.vtt |
13.97Кб |
| 7. Convolution with time-domain Gaussian (smoothing filter).mp4 |
49.48Мб |
| 7. Convolution with time-domain Gaussian (smoothing filter).vtt |
7.27Кб |
| 7. Extrapolation.mp4 |
36.67Мб |
| 7. Extrapolation.vtt |
7.15Кб |
| 7. Full width at half-maximum.mp4 |
131.28Мб |
| 7. Full width at half-maximum.vtt |
21.48Кб |
| 7. Link to youtube channel with 3 hours of relevant material.html |
621б |
| 7. Magnitude and phase of complex numbers.mp4 |
48.31Мб |
| 7. Magnitude and phase of complex numbers.vtt |
9.40Кб |
| 7. Remove linear trend (detrending).mp4 |
12.85Мб |
| 7. Remove linear trend (detrending).vtt |
2.62Кб |
| 8. Code challenge find the features!.mp4 |
24.01Мб |
| 8. Code challenge find the features!.vtt |
4.06Кб |
| 8. Convolution with frequency-domain Gaussian (narrowband filter).mp4 |
51.82Мб |
| 8. Convolution with frequency-domain Gaussian (narrowband filter).vtt |
8.11Кб |
| 8. Data length and filter kernel length.mp4 |
65.02Мб |
| 8. Data length and filter kernel length.vtt |
9.83Кб |
| 8. MATLAB Time-frequency analysis with complex wavelets.mp4 |
140.35Мб |
| 8. MATLAB Time-frequency analysis with complex wavelets.vtt |
17.75Кб |
| 8. Remove nonlinear trend with polynomials.mp4 |
109.31Мб |
| 8. Remove nonlinear trend with polynomials.vtt |
18.17Кб |
| 8. Spectral interpolation.mp4 |
77.28Мб |
| 8. Spectral interpolation.vtt |
12.46Кб |
| 9. Averaging multiple repetitions (time-synchronous averaging).mp4 |
49.75Мб |
| 9. Averaging multiple repetitions (time-synchronous averaging).vtt |
6.48Кб |
| 9. Convolution with frequency-domain Planck taper (bandpass filter).mp4 |
46.06Мб |
| 9. Convolution with frequency-domain Planck taper (bandpass filter).vtt |
7.46Кб |
| 9. Dynamic time warping.mp4 |
122.58Мб |
| 9. Dynamic time warping.vtt |
19.71Кб |
| 9. Low-pass filters.mp4 |
64.01Мб |
| 9. Low-pass filters.vtt |
8.86Кб |
| 9. Time-frequency analysis of brain signals.mp4 |
63.48Мб |
| 9. Time-frequency analysis of brain signals.vtt |
9.90Кб |
| ReadMe.txt |
241б |
| ReadMe.txt |
241б |
| Visit Freecourseit.com.url |
342б |
| Visit Getnewcourses.com.url |
343б |