By Topic

An advanced neuron model for optimizing the SIREN network architecture

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
M. Alderighi ; Istituto di Fisica Cosmica e Tecnologie Realtive, CNR, Milano, Italy ; S. D'Angelo ; F. d'Ovidio ; E. Gummati
more authors

The paper presents a computational system based on a synchronous feedback neural network for the on-line event processing of a photon counting intensified CCD. The project is based on a neuron model that improves the one already defined for the SIgnal REcognition Network (SIREN) system and on a suitable network architecture. As far as the neuron is concerned, a new equation for network dynamics is envisaged, that allows to reduce the number of cycles needed for event identification. As far as the architecture is concerned, we focus on the definition of a network having less neurons than SIREN while maintaining the same performance. An hypothesis of network architecture and a performance comparison between the two neural models are given in the paper

Published in:

Algorithms & Architectures for Parallel Processing, 1996. ICAPP 96. 1996 IEEE Second International Conference on

Date of Conference:

11-13 Jun 1996