Download Signal Processing Solutions With Python torrent

Signal Processing Solutions With Python

Torrent:	Signal Processing Solutions With Python
Description:	Description This course will bridge the gap between the theory of signal processing and implementation in Python. All the lecture slides and python codes are provided. Why Signal Processing? Since the availability of digital computers in the 1970s, digital signal processing has found its way in all sections of engineering and sciences. Signal processing is the manipulation of the basic nature of a signal to get the desired shaping of the signal at the output. It is concerned with the representation of signals by a sequence of numbers or symbols and the processing of these signals. Following areas of sciences and engineering are specially benefitted by rapid growth and advancement in signal processing techniques. 1. Machine Learning. 2. Data Analysis. 3. Computer Vision. 4. Image Processing and Medical Imaging. 5. Communication Systems. 6. Power Electronics. 7. Probability and Statistics. 8. Numerical Analysis. 9. Decision Theory. 10. Integrated Circuit design. What you will learn from the course 1. Fundamentals of signals and signal Processing. 2. Analog to digital conversion. 3. Sampling and Reconstruction. 4. Nyquist Theorem. 5. The Convolution. 6. Signal denoising. 7. Fourier transform. 8. Signal filtering by FIR and IIR filters. 9. Implementing all signal processing techniques with python. Course Outline Section 01 : Introduction of the course Section 02 : Python crash course Section 03 : Fundamentals of Signal Processing Section 04 : Convolution Section 05 : Signal Denoising Section 06: Complex Numbers Section 07 : Fourier Transform Section 08 : FIR Filter Design Section 09 : IIR Filter Design Who this course is for: University students taking signal processing course. Engineers and scientists working in the signal processing area. Engineers and scientists who know the Maths of signal processing and want to learn the implementations in Python. People who want to know about data and time series filtering. People who know implementation of signal processing algorithms in Matlab and want to switch to the Python. Requirements Some fundamental knowledge of programming may be helpful but not necessary. Last Updated 8/2021
Downloads:	130
Category:	Other /Tutorials
Size:	4.6 GB
Show Files »	Signal Processing Solutions With Python [TutsNode.com] - Signal Processing Solutions With Python 07 Fourier Transform 005 Step by step coding of Fourier Transform.mp4 (180.5 MB) 005 Step by step coding of Fourier Transform.en.srt (34.2 KB) 004 Mechanism of Fourier Transform.en.srt (26.0 KB) 003 Generating Waves in Python.en.srt (17.8 KB) 002 Combining Sine and Cosine Waves.en.srt (14.2 KB) 007 FT of signal with DC component.en.srt (13.3 KB) 006 Fast Fourier Transform.en.srt (11.3 KB) 008 Amplitude and Power Spectrum.en.srt (11.2 KB) 009 Inverse Fourier Transform.en.srt (8.1 KB) 011 Application of FT _ Signal stationarity Part-02.en.srt (6.8 KB) 010 Application of FT _ Signal stationarity Part-01.en.srt (6.5 KB) 001 Introduction of the section.en.srt (2.2 KB) 004 Mechanism of Fourier Transform.mp4 (112.7 MB) 003 Generating Waves in Python.mp4 (97.9 MB) 007 FT of signal with DC component.mp4 (64.5 MB) 002 Combining Sine and Cosine Waves.mp4 (60.5 MB) 006 Fast Fourier Transform.mp4 (50.2 MB) 008 Amplitude and Power Spectrum.mp4 (46.1 MB) 009 Inverse Fourier Transform.mp4 (38.9 MB) 011 Application of FT _ Signal stationarity Part-02.mp4 (32.1 MB) 010 Application of FT _ Signal stationarity Part-01.mp4 (28.1 MB) 001 Introduction of the section.mp4 (9.0 MB) 08 FIR Filter Design 003 Steps for designing FIR filters.en.srt (33.9 KB) 004 FIR filter design by Least Square Method.en.srt (17.0 KB) 006 FIR Zero Shift Filter.en.srt (16.4 KB) 008 Low Pass FIR filter in Python.en.srt (13.4 KB) 007 Low Pass FIR filter.en.srt (10.8 KB) 002 Introduction to digital filters.en.srt (10.6 KB) 012 Band Pass FIR filter in Python.en.srt (9.7 KB) 005 FIR filter design by Window Method.en.srt (9.3 KB) 011 Band Pass FIR filter.en.srt (8.8 KB) 010 High Pass FIR filter in Python.en.srt (8.8 KB) 009 High Pass FIR filter.en.srt (8.6 KB) 001 Introduction of the section.en.srt (2.9 KB) 013 Tasks for students.en.srt (2.0 KB) 003 Steps for designing FIR filters.mp4 (100.6 MB) 006 FIR Zero Shift Filter.mp4 (87.1 MB) 004 FIR filter design by Least Square Method.mp4 (85.4 MB) 008 Low Pass FIR filter in Python.mp4 (67.6 MB) 012 Band Pass FIR filter in Python.mp4 (57.4 MB) 010 High Pass FIR filter in Python.mp4 (49.4 MB) 005 FIR filter design by Window Method.mp4 (46.0 MB) 002 Introduction to digital filters.mp4 (45.7 MB) 007 Low Pass FIR filter.mp4 (36.7 MB) 009 High Pass FIR filter.mp4 (30.6 MB) 011 Band Pass FIR filter.mp4 (29.1 MB) 001 Introduction of the section.mp4 (7.1 MB) 013 Tasks for students.mp4 (4.8 MB) 04 The Convolution 005 Convolution using for loop in Python.en.srt (30.0 KB) 003 Numerical Example on convolution.en.srt (23.6 KB) 002 The Convolution Sum.en.srt (22.3 KB) 005 Convolution using for loop in Python.mp4 (140.2 MB) 007 Application 01 _ Signal denoising using Convolution.en.srt (14.7 KB) 009 Convolution Theorem.en.srt (11.2 KB) 001 Introduction of the section.en.srt (2.4 KB) 008 Application 02 _ Edge detection using Convolution.en.srt (8.6 KB) 006 Convolution using NumPy.en.srt (7.3 KB) 004 Full mode convolution.en.srt (3.8 KB) 007 Application 01 _ Signal denoising using Convolution.mp4 (84.8 MB) 003 Numerical Example on convolution.mp4 (63.1 MB) 002 The Convolution Sum.mp4 (62.3 MB) 009 Convolution Theorem.mp4 (51.2 MB) 006 Convolution using NumPy.mp4 (42.3 MB) 008 Application 02 _ Edge detection using Convolution.mp4 (37.1 MB) 004 Full mode convolution.mp4 (8.6 MB) 001 Introduction of the section.mp4 (8.2 MB) 05 Signal Denoising 009 Removing Spiky Noise by Median Filter in Python Part-01.en.srt (27.2 KB) 005 Gaussian Mean Filter in Python.en.srt (24.3 KB) 003 Moving Average Filter in Python.en.srt (18.9 KB) 004 Gaussian Mean Filter.en.srt (11.8 KB) 010 Removing Spiky Noise by Median Filter in Python Part-02.en.srt (10.8 KB) 002 Moving Average Filter.en.srt (9.9 KB) 006 Median Filter.en.srt (9.5 KB) 007 Median Filter in Python.en.srt (8.8 KB) 008 Removing Spiky Noise by Median Filter.en.srt (6.0 KB) 001 Introduction of the section.en.srt (2.9 KB) 005 Gaussian Mean Filter in Python.mp4 (139.9 MB) 009 Removing Spiky Noise by Median Filter in Python Part-01.mp4 (117.4 MB) 003 Moving Average Filter in Python.mp4 (96.8 MB) 010 Removing Spiky Noise by Median Filter in Python Part-02.mp4 (53.5 MB) 007 Median Filter in Python.mp4 (49.5 MB) 004 Gaussian Mean Filter.mp4 (46.8 MB) 002 Moving Average Filter.mp4 (41.3 MB) 006 Median Filter.mp4 (33.5 MB) 008 Removing Spiky Noise by Median Filter.mp4 (22.6 MB) 001 Introduction of the section.mp4 (6.0 MB) 01 Introduction of the course 003 Course Material.html (1.0 KB) 001 Introduction of the course.en.srt (6.5 KB) 002 Pace of Lecture delivery.en.srt (3.3 KB) 001 Introduction of the course.mp4 (23.3 MB) 002 Pace of Lecture delivery.mp4 (18.2 MB) 003 Course Material.zip (16.8 MB) 02 Python Crash Course 001 Introduction of the section.en.srt (1.3 KB) 016 For Loops - Part01.en.srt (25.7 KB) 015 Lists in Python.en.srt (25.6 KB) 017 For Loops - Part02.en.srt (25.5 KB) 010 Dealing with arrays-Part03.en.srt (24.1 KB) 011 Plotting and Visualization-Part01.en.srt (20.8 KB) 012 Plotting and Visualization-Part02.en.srt (17.8 KB) 003 Introduction of Jupyter Notebook.en.srt (17.5 KB) 013 Plotting and Visualization-Part03.en.srt (16.9 KB) 009 Dealing with arrays-Part02.en.srt (13.7 KB) files
Added:	2021-08-25 11:12:20
Language:	English
Peers:	Seeders : 23 , Leechers : 10
Release name:	Signal Processing Solutions With Python
Trackers:	udp://inferno.demonoid.pw:3391/announce udp://tracker.openbittorrent.com:80/announce udp://tracker.opentrackr.org:1337/announce udp://torrent.gresille.org:80/announce udp://glotorrents.pw:6969/announce udp://tracker.leechers-paradise.org:6969/announce udp://tracker.pirateparty.gr:6969/announce udp://tracker.coppersurfer.tk:6969/announce udp://ipv4.tracker.harry.lu:80/announce udp://9.rarbg.to:2710/announce udp://shadowshq.yi.org:6969/announce udp://tracker.zer0day.to:1337/announce