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1/7/2021
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Signal processing problems, solved in MATLAB and in Python is a training course from Udemy site that solves problems related to signal processing and DSP using MATLAB and Python. Nature is very complex and mysterious and one of the biggest challenges in understanding it is data analysis. Nature has a great tendency to combine signal and noise sources, and this makes it more difficult to understand nature. Therefore, one of the most important goals of temporal data analysis and signal processing is noise isolation.
One of the biggest ideas of DSP or digital signal processing is to discover the secrets hidden in the time data and this course tries to show you the most common ways to discover these secrets. The main focus of this course is on the implementation of signal processing techniques in MATLAB and Python. In this course, you will encounter more than 10,000 lines of MATLAB and Python code and you will learn the topics related to signal processing well.
Familiarity with the most common signal processing tools
Design, evaluate, and apply digital filters
Cleansing and isolating noise from data
Improve MATLAB and Python programming skills
Production of experimental signals
English language
Duration: 12 hours and 26 minutes
Number of courses: 98
Level of education: Intermediate
Instructor: Mike X Cohen
File format: mp4
98 lectures 12:26:42
Introductions 7 lectures 35:24
Time series denoising 11 lectures 01:17:22
Spectral and rhythmicity analyses 6 lectures 01:00:17
Working with complex numbers 7 lectures 35:56
Filtering 17 lectures 02:23:57
Convolution 10 lectures 01:11:20
Wavelet analysis 10 lectures 01:06:03
Resampling, interpolating, extrapolating 10 lectures 01:27:50
Outlier detection 5 lectures 27:10
Feature detection 8 lectures 01:30:23
Variability 6 lectures 50:14
Bonus section 1 lecture 00:41
Basic programming experience in MATLAB or Python
High-school math
After Extract, watch with your favorite Player.
English subtitle
Quality: 720p
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