• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar

ALLSIGNALPROCESSING.COM

Learn signal processing online

  • Home
  • Courses
  • Courses
  • About
  • FAQ
  • My Account
  • Blog
  • News
  • Contact
  • Login
  • Logout
  • Get All Access

Convergence, Tracking, and the LMS Algorithm Step Size

August 10, 2019 by

There is only one parameter in the LMS algorithm that is chosen by you: the step size. You need to understand how the step-size parameter impacts the performance characteristics of the LMS algorithm in order to use it effectively.

The step-size parameter determines whether the algorithm converges or diverges and how fast. It also determines the steady-state behavior and how fast the algorithm responds to changes in the characteristics of the data. This lesson explores these aspects from an intuitive point of view and provides you with the insight you need to apply LMS.

Click here to purchase immediate access to this and every other (more than 120) lesson!

Primary Sidebar

Courses

  • Foundations

  • Time Domain LTI Systems

  • Fourier Series and Transforms

  • Sampling and Reconstruction

  • The DFT and Applications

  • The Z-Transform

  • Intro to Filter Design

  • IIR Filter Design

  • FIR Filter Design

  • Random Signal Characterization

  • Basis Representations of Signals

  • Estimation of Power Spectra and Coherence

  • Introduction to Signal Estimation and Detection Theory

  • MMSE Filtering and Least-Squares Problems

Copyright © 2023 ALLSIGNALPROCESSING.COM | Site Design by 3200 Creative

  • Terms of Service
  • Privacy Policy
  • Contact