Next  |  Index  |  JOS Index  |  JOS Pubs  |  JOS Home  |  Search

Elementary Gradient-Based Parameter Estimation

JULIUS O. SMITH III

Center for Computer Research in Music and Acoustics (CCRMA)
Department of Music, Stanford University, Stanford, California 94305 USA

Abstract:

This section defines some of the basic terms involved in optimization techniques known as gradient descent and Newton's method. Terms defined include metric space, linear space, norm, pseudo-norm, normed linear space, Banach space, Lp space, Hilbert space, functional, convex norm, concave norm, local minimizer, global minimizer, and Taylor series expansion.

Detailed Contents (and Navigation)


Next  |  Index  |  JOS Index  |  JOS Pubs  |  JOS Home  |  Search

Download gradient.pdf
Download the whole thesis containing this material.

``Elementary Gradient-Based Parameter Estimation'', by Julius O. Smith III, from ``Techniques for Digital Filter Design and System Identification, with Application to the Violin,'' Julius O. Smith III, Ph.D. Dissertation, CCRMA, Department of Electrical Engineering, Stanford University, June 1983.
Copyright © 2006-01-03 by Julius O. Smith III
Center for Computer Research in Music and Acoustics (CCRMA),   Stanford University
CCRMA  [Automatic-links disclaimer]