Neural networks as spatio-temporal pattern-forming systems

Neural networks as spatio-temporal pattern-forming systems

Models of neural networks are developed from a biological point of view. Small networks are analysed using techniques from dynamical systems. The behaviour of spatially and temporally organized neural fields is then discussed from the point of view of pattern formation. Bifurcation methods, analytic solutions and perturbation methods are applied to these models. 0034-4885/98/040353+78$59.50 c ©...

Neural Nets as Spatio-temporal Pattern Forming Systems

Spatio-Temporal Pattern Recognition with Neural Networks: Application to Speech

The processing or the recognition of non stationary process with neural networks is a challenging and yet unsolved issue. The paper discuss the general pattern recognition framework using neural networks in relation with the understanding of the peripheral auditory system. We propose a short-time structure representation of speech for speech analysis and recognition. We give examples of neural ...

Distribution Systems Reconfiguration Using Pattern Recognizer Neural Networks

A novel intelligent neural optimizer with two objective functions is designed for electrical distribution systems. The presented method is faster than alternative optimization methods and is comparable with the most powerful and precise ones. This optimizer is much smaller than similar neural systems. In this work, two intelligent estimators are designed, a load flow program is coded, and a spe...

Dynamic evolving spiking neural networks for on-line spatio- and spectro-temporal pattern recognition.

On-line learning and recognition of spatio- and spectro-temporal data (SSTD) is a very challenging task and an important one for the future development of autonomous machine learning systems with broad applications. Models based on spiking neural networks (SNN) have already proved their potential in capturing spatial and temporal data. One class of them, the evolving SNN (eSNN), uses a one-pass...