A highly efficient implementation of a backpropagation learning algorithm using matrix ISA-Reference-Cited by-同舟云学术

A highly efficient implementation of a backpropagation learning algorithm using matrix ISA

Published:2008-07 Issue:7 Volume:68 Page:949-961
ISSN:0743-7315
Container-title:Journal of Parallel and Distributed Computing
language:en
Short-container-title:Journal of Parallel and Distributed Computing

Author:

Soliman Mostafa I.,Mohamed Samir A.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture,Theoretical Computer Science,Software

Reference35 articles.

1. N. Ampazis, S.J. Perantonis, Levenberg–Marquardt algorithm with adaptive momentum for efficient training for feed forward networks, in: Proc. International Joint Conference on Neural Networks, IJCNN, Italy, 2000

2. Davide Anguita, MBP: A matrix back propagation V1.1: An efficient implementation of the BP algorithm, Technical Report, DIBE, University of Genova, Italy, 1993

3. Davide Anguita, B. Gomes, MBP on T0: mixing floating- and fixed-point formats in BP learning, Technical Report No. TR-94-038, International Computer Science Institute, Berkeley, 1994

4. K. Asanovic, Vector microprocessors, Ph.D. Thesis, Computer Science Division, University of California at Berkeley, 1998

5. The μVP 64-bit vector coprocessor: A new implementation of high-performance numerical computation;Awaga;IEEE Micro,1993

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Parallel BP Neural Network Based on the FPGA;Applied Mechanics and Materials;2012-12

2. Reducing Feed-Forward Neural Network Processing Time Utilizing Matrix Multiplication Algorithms on Heterogeneous Distributed Systems;2009 First International Conference on Computational Intelligence, Communication Systems and Networks;2009-07