Wavelet Analysis: Concepts with Wolfram Language
With Wolfram Research
Liked by 12 users
Duration: 49m
Skill level: Intermediate
Released: 1/4/2024
Course details
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.
Skills you’ll gain
Earn a sharable certificate
Share what you’ve learned, and be a standout professional in your desired industry with a certificate showcasing your knowledge gained from the course.
LinkedIn Learning
Certificate of Completion
-
Showcase on your LinkedIn profile under “Licenses and Certificate” section
-
Download or print out as PDF to share with others
-
Share as image online to demonstrate your skill
Meet the instructor
Contents
What’s included
- Learn on the go Access on tablet and phone