Wavelet Analysis: Concepts with Wolfram Language
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Wolfram Research
49:09
12 View
01 - Introduction.mp4
09:41
01 - Continuous wavelet transform.mp4
10:36
01 - Discrete wavelets.mp4
05:10
01 - Wavelet filter bank.mp4
03:28
01 - Discrete wavelet data.mp4
07:02
01 - Wavelet best basis.mp4
04:28
01 - Wavelet thresholding.mp4
07:40
01 - References.mp4
01:04
Description
Wavelets decompose a signal into approximations and details at different scales, making them useful for applications such as data compression, detecting features and removing noise from signals. This course from Wolfram Research explains some of the theory behind continuous, discrete, and stationary wavelet transforms and demonstrates how the Wolfram Language and its built-in functions can be used to construct, compute, visualize, and analyze wavelet transforms and related functions.
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Wolfram Research
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Linkedin Learning
View courses Linkedin LearningLinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications.
It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.
- language english
- Training sessions 8
- duration 49:09
- English subtitles has
- Release Date 2024/04/20
