Dynamical aspects of multi-time scale unsupervised neural networks

Anke Meyer-Bäse; Shantanu Joshi; Helge Ritter

doi:10.1117/12.668681

9 May 2006 Dynamical aspects of multi-time scale unsupervised neural networks

Anke Meyer-Bäse, Shantanu Joshi, Helge Ritter

Proceedings Volume 6229, Intelligent Computing: Theory and Applications IV; 62290V (2006) https://doi.org/10.1117/12.668681
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

Multi-time scale unsupervised neural networks (MTSUNN) represent an established technique in pattern recognition for feature extraction and cluster analysis. From the nonlinear systems analysis perspective, they implement a very complex coupled multi-mode dynamics. This paper gives a comprehensive overview of several neural architectures of a combined activity and weights dynamics. The global asymptotic and exponential stability of the equilibrium points of these continuous-time recurrent systems whose weights are adapted based on unsupervised learning laws are mathematically analyzed. The derived architectures can lead to hybrid implementations in VLSI techniques.

Citation Download Citation

Anke Meyer-Bäse, Shantanu Joshi, and Helge Ritter "Dynamical aspects of multi-time scale unsupervised neural networks", Proc. SPIE 6229, Intelligent Computing: Theory and Applications IV, 62290V (9 May 2006); https://doi.org/10.1117/12.668681

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available