Convergence properties of SOFM algorithm for vector quantization

Siming Lin; Jennie Si

Convergence properties of SOFM algorithm for vector quantization

Siming Lin
, Jennie Si

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we present new results to the literature on convergence properties of the self-organizing feature map (SOFM) as a multi-dimensional vector quantizer using Robbins-Monro stochastic approximation principle. It is shown that the weights of the SOFM algorithm converge almost truly to the centroids of the cells of a Voronoi partition of the input space if the neighborhood function satisfies some reasonable conditions. The range of neighborhood functions in the SOFM algorithm is interpreted as a control parameter for an annealing process. Computer simulations were performed to demonstrate the convergence properties of the SOFM.

Original language	English (US)
Title of host publication	Proceedings - IEEE International Symposium on Circuits and Systems
Editors	Anon
Publisher	IEEE
Pages	509-512
Number of pages	4
Volume	1
State	Published - 1997
Event	Proceedings of the 1997 IEEE International Symposium on Circuits and Systems, ISCAS'97. Part 4 (of 4) - Hong Kong, Hong Kong Duration: Jun 9 1997 → Jun 12 1997

Other

Other	Proceedings of the 1997 IEEE International Symposium on Circuits and Systems, ISCAS'97. Part 4 (of 4)
City	Hong Kong, Hong Kong
Period	6/9/97 → 6/12/97

ASJC Scopus subject areas

Electrical and Electronic Engineering
Electronic, Optical and Magnetic Materials

Cite this

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title = "Convergence properties of SOFM algorithm for vector quantization",

abstract = "In this paper, we present new results to the literature on convergence properties of the self-organizing feature map (SOFM) as a multi-dimensional vector quantizer using Robbins-Monro stochastic approximation principle. It is shown that the weights of the SOFM algorithm converge almost truly to the centroids of the cells of a Voronoi partition of the input space if the neighborhood function satisfies some reasonable conditions. The range of neighborhood functions in the SOFM algorithm is interpreted as a control parameter for an annealing process. Computer simulations were performed to demonstrate the convergence properties of the SOFM.",

author = "Siming Lin and Jennie Si",

year = "1997",

language = "English (US)",

volume = "1",

pages = "509--512",

editor = "Anon",

booktitle = "Proceedings - IEEE International Symposium on Circuits and Systems",

publisher = "IEEE",

note = "Proceedings of the 1997 IEEE International Symposium on Circuits and Systems, ISCAS'97. Part 4 (of 4) ; Conference date: 09-06-1997 Through 12-06-1997",

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T1 - Convergence properties of SOFM algorithm for vector quantization

AU - Lin, Siming

AU - Si, Jennie

PY - 1997

Y1 - 1997

N2 - In this paper, we present new results to the literature on convergence properties of the self-organizing feature map (SOFM) as a multi-dimensional vector quantizer using Robbins-Monro stochastic approximation principle. It is shown that the weights of the SOFM algorithm converge almost truly to the centroids of the cells of a Voronoi partition of the input space if the neighborhood function satisfies some reasonable conditions. The range of neighborhood functions in the SOFM algorithm is interpreted as a control parameter for an annealing process. Computer simulations were performed to demonstrate the convergence properties of the SOFM.

AB - In this paper, we present new results to the literature on convergence properties of the self-organizing feature map (SOFM) as a multi-dimensional vector quantizer using Robbins-Monro stochastic approximation principle. It is shown that the weights of the SOFM algorithm converge almost truly to the centroids of the cells of a Voronoi partition of the input space if the neighborhood function satisfies some reasonable conditions. The range of neighborhood functions in the SOFM algorithm is interpreted as a control parameter for an annealing process. Computer simulations were performed to demonstrate the convergence properties of the SOFM.

UR - https://www.scopus.com/pages/publications/0030703872

UR - https://www.scopus.com/pages/publications/0030703872#tab=citedBy

M3 - Conference contribution

VL - 1

SP - 509

EP - 512

BT - Proceedings - IEEE International Symposium on Circuits and Systems

A2 - Anon, null

PB - IEEE

T2 - Proceedings of the 1997 IEEE International Symposium on Circuits and Systems, ISCAS'97. Part 4 (of 4)

Y2 - 9 June 1997 through 12 June 1997

ER -

Convergence properties of SOFM algorithm for vector quantization

Abstract

Other

ASJC Scopus subject areas

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