Download Signal Processing Solutions With Python torrent

Signal Processing Solutions With Python

Torrent:	Signal Processing Solutions With Python
Description:	Signal Processing Solutions With Python MP4 \| Video: h264, 1280x720 \| Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning \| Language: English + srt \| Duration: 91 lectures (14h 13m) \| Size: 3.86 GB Applied Signal Processing With Python What you'll learn: Fundamentals of Signal Processing. Sampling and Reconstruction Nyquist Theorem Convolution Signal Denoising Fourier Transform and its Application Designing of FIR and IIR Filters Implementation of all above algorithms with Python Requirements Some fundamental knowledge of programming may be helpful but not necessary. 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.
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Category:	Other /Tutorials
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Show Files »	Signal Processing Solutions With Python !!! More Courses !!!.txt (1.1 KB) 01 Introduction of the course 001 Introduction of the course.en.srt (6.5 KB) 001 Introduction of the course.mp4 (23.3 MB) 002 Pace of Lecture delivery.en.srt (3.3 KB) 002 Pace of Lecture delivery.mp4 (18.2 MB) 003 Course Material.html (1.0 KB) 003 Course Material.zip (16.8 MB) Visit My Blog.url (0.1 KB) 02 Python Crash Course 001 Introduction of the section.en.srt (1.3 KB) 001 Introduction of the section.mp4 (3.1 MB) 002 Python Installment.en.srt (5.5 KB) 002 Python Installment.mp4 (25.0 MB) 003 Introduction of Jupyter Notebook.en.srt (17.5 KB) 003 Introduction of Jupyter Notebook.mp4 (52.1 MB) 004 Installing Python Packages.en.srt (5.5 KB) 004 Installing Python Packages.mp4 (16.7 MB) 005 Arithmatic with Python- Part 01.en.srt (9.3 KB) 005 Arithmatic with Python- Part 01.mp4 (35.0 MB) 006 Arithmatic with Python- Part 02.en.srt (11.7 KB) 006 Arithmatic with Python- Part 02.mp4 (40.2 MB) 007 Arithmatic with Python- Part 03.en.srt (9.9 KB) 007 Arithmatic with Python- Part 03.mp4 (31.9 MB) 007 Installing Packages.docx (12.4 KB) 008 Dealing with Arrays-Part01.en.srt (13.1 KB) 008 Dealing with Arrays-Part01.mp4 (57.2 MB) 009 Dealing with arrays-Part02.en.srt (13.7 KB) 009 Dealing with arrays-Part02.mp4 (58.3 MB) 010 Dealing with arrays-Part03.en.srt (24.1 KB) 010 Dealing with arrays-Part03.mp4 (119.2 MB) 011 Plotting and Visualization-Part01.en.srt (20.8 KB) 011 Plotting and Visualization-Part01.mp4 (96.3 MB) 012 Plotting and Visualization-Part02.en.srt (17.8 KB) 012 Plotting and Visualization-Part02.mp4 (123.0 MB) 013 Plotting and Visualization-Part03.en.srt (16.9 KB) 013 Plotting and Visualization-Part03.mp4 (78.1 MB) 014 Plotting and Visualization-Part04.en.srt (9.0 KB) 014 Plotting and Visualization-Part04.mp4 (54.2 MB) 015 Lists in Python.en.srt (25.6 KB) 015 Lists in Python.mp4 (89.0 MB) 016 For Loops - Part01.en.srt (25.7 KB) 016 For Loops - Part01.mp4 (87.1 MB) 017 For Loops - Part02.en.srt (25.5 KB) 017 For Loops - Part02.mp4 (92.4 MB) Visit My Blog.url (0.1 KB) 03 Analog to Digital Conversion 001 Introduction of the section.en.srt (2.5 KB) 001 Introduction of the section.mp4 (7.9 MB) 002 Elements of signal processing system.en.srt (11.4 KB) 002 Elements of signal processing system.mp4 (49.8 MB) 003 AD Conversion.en.srt (20.9 KB) 003 AD Conversion.mp4 (73.6 MB) 004 AD Conversion With Python.en.srt (13.7 KB) 004 AD Conversion With Python.mp4 (74.1 MB) 005 Quantized to digital conversion.en.srt (4.6 KB) 005 Quantized to digital conversion.mp4 (14.0 MB) 006 Fundamental Continuous time signal.en.srt (20.3 KB) 006 Fundamental Continuous time signal.mp4 (58.7 MB) 007 Continuous time signals in Python.en.srt (21.7 KB) 007 Continuous time signals in Python.mp4 (118.1 MB) 008 Fundamental Discrete time signals.en.srt (9.6 KB) 008 Fundamental Discrete time signals.mp4 (25.1 MB) 009 Discrete time signals in Python.en.srt (20.7 KB) 009 Discrete time signals in Python.mp4 (101.7 MB) 010 Sampling and Reconstruction.en.srt (12.5 KB) 010 Sampling and Reconstruction.mp4 (61.1 MB) 011 Sampling and Reconstruction in Python.en.srt (16.3 KB) 011 Sampling and Reconstruction in Python.mp4 (98.7 MB) Visit My Blog.url (0.1 KB) 04 The Convolution 001 Introduction of the section.en.srt (2.4 KB) 001 Introduction of the section.mp4 (8.2 MB) 002 The Convolution Sum.en.srt (22.3 KB) 002 The Convolution Sum.mp4 (62.3 MB) 003 Numerical Example on convolution.en.srt (23.6 KB) 003 Numerical Example on convolution.mp4 (63.1 MB) 004 Full mode convolution.en.srt (3.8 KB) 004 Full mode convolution.mp4 (8.6 MB) 005 Convolution using for loop in Python.en.srt (30.0 KB) 005 Convolution using for loop in Python.mp4 (140.2 MB) 006 Convolution using NumPy.en.srt (7.3 KB) 006 Convolution using NumPy.mp4 (42.3 MB) 007 Application 01 _ Signal denoising using Convolution.en.srt (14.7 KB) 007 Application 01 _ Signal denoising using Convolution.mp4 (84.8 MB) 008 Application 02 _ Edge detection using Convolution.en.srt (8.6 KB) 008 Application 02 _ Edge detection using Convolution.mp4 (37.1 MB) 009 Convolution Theorem.en.srt (11.2 KB) 009 Convolution Theorem.mp4 (51.2 MB) Visit My Blog.url (0.1 KB) 05 Signal Denoising 001 Introduction of the section.en.srt (2.9 KB) 001 Introduction of the section.mp4 (6.0 MB) 002 Moving Average Filter.en.srt (9.9 KB) 002 Moving Average Filter.mp4 (41.3 MB) 003 Moving Average Filter in Python.en.srt (18.9 KB) 003 Moving Average Filter in Python.mp4 (96.8 MB) 004 Gaussian Mean Filter.en.srt (11.8 KB) 004 Gaussian Mean Filter.mp4 (46.8 MB) 005 Gaussian Mean Filter in Python.en.srt (24.3 KB) 005 Gaussian Mean Filter in Python.mp4 (139.9 MB) 006 Median Filter.en.srt (9.5 KB) 006 Median Filter.mp4 (33.5 MB) 007 Median Filter in Python.en.srt (8.8 KB) 007 Median Filter in Python.mp4 (49.5 MB) 008 Removing Spiky Noise by Median Filter.en.srt (6.0 KB) 008 Removing Spiky Noise by Median Filter.mp4 (22.6 MB) 009 Removing Spiky Noise by Median Filter in Python Part-01.en.srt (27.2 KB) 009 Removing Spiky Noise by Median Filter in Python Part-01.mp4 (117.4 MB) 010 Removing Spiky Noise by Median Filter in Python Part-02.en.srt (10.8 KB) 010 Removing Spiky Noise by Median Filter in Python Part-02.mp4 (53.5 MB) files
Added:	2021-08-16 11:06:59
Language:	English
Peers:	Seeders : 2 , Leechers : 1
Tags:	Courses Tutorials Coursesghar
Release name:	Signal Processing Solutions With Python
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