@inproceedings{de14a5b12ba84afcb5a75b7cda699fa1,
title = "Artificial neural networks on reconfigurable meshes",
abstract = "Artificial neural networks(ANN) have been used successfully in applications such as pattern recognition, image processing, automation and control. Majority of today{\textquoteright}s applications use backpropagate feedforward ANN. In this paper, two methods of P pattern L layer ANN learning on n x n RMESH have been presented. One required memory space of O(nL) but conceptually is simpler to develop and the other uses pipelined approach which reduces the memory requirement to O(L). Both of these algorithms take O(PL) time and are optimal for RMESH architecture.",
keywords = "Artificial neural networks, Parallel algorithms, Reconfigurable mesh algorithms",
author = "Jenq, {Jing Fu} and Li, {Wing Ning}",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1998.; 10 Workshops held in conjunction with 12th International Parallel Symposium and 9th Symposium on Parallel and Distributed Processing, IPPS/SPDP 1998 ; Conference date: 30-03-1998 Through 03-04-1998",
year = "1998",
doi = "10.1007/3-540-64359-1_693",
language = "English",
isbn = "3540643591",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "234--242",
editor = "Jose Rolim",
booktitle = "Parallel and Distributed Processing - 10 IPPS/SPDP 1998 Workshops Held in Conjunction with the 12th International Parallel Processing Symposium and 9th Symposium on Parallel and Distributed Processing, Proceedings",
}