Professional Courses
Industry-relevant training in Business, Technology, and Design
Categories
Interactive Games
Fun games to boost memory, math, typing, and English skills
Typing
Memory
Math
English Adventures
Knowledge
Digital Signal Processing
Adaptive filters play a crucial role in signal processing by enabling tasks such as equalization and noise cancellation. These filters continuously adjust their parameters based on incoming signals, making them effective in dynamic environments. The Least Mean Squares (LMS) algorithm is a prevalent method for updating filter coefficients, enhancing the quality of transmitted signals by mitigating distortions and eliminating unwanted noise.
12 Chapters
24 Weeks
We're sorry, but this course is currently unavailable. It may have expired, be pending
approval, or still be processing
your enrollment. Please check back later or contact your instructor or support for
assistance.
Course Chapters
Chapter 1
Discrete-Time Signals and Systems: Convolution and Correlation
Chapter 2
Sampling, Reconstruction, and Aliasing
Chapter 3
Sampling, Reconstruction, and Aliasing: Time and Frequency Domains
Chapter 4
Time and Frequency Domains: Z-Transform
Chapter 5
FIR Filters: Moving Average Filters
Chapter 6
FIR Filters: Window Method of Design
Chapter 7
IIR Filters: Impulse Invariant and Bilinear Transform Methods of Design
Chapter 8
IIR Filters: Simple Design Example
Chapter 9
Fast Fourier Transform: Review of Fourier Analysis
Chapter 10
Fast Fourier Transform: Derivation of the Radix-2 FFT
Chapter 11
Adaptive Filters: Prediction and System Identification
Chapter 12