PIPELINED ON-LINE BACK-PROPAGATION TRAINING OF AN ARTIFICIAL NEURAL NETWORK ON A PARALLEL MULTIPROCESSOR SYSTEM

Título: PIPELINED ON-LINE BACK-PROPAGATION TRAINING OF AN ARTIFICIAL NEURAL NETWORK ON A PARALLEL MULTIPROCESSOR SYSTEM

Autores: Silva, Tiago Mendonça; Braga, Antônio de Pádua; Lacerda, Wilian Soares

Resumo: This work presents an on-chip learning of artifícial neural networks in a FPGA multiprocessor system, where each neuron is implemented in a soft-core processor. In order to take maximum advantage of the distributed architecture, a pipelined version of the on-line back-propagation algorithm is used, providing a high degree of parallelism between neuron layers and, hence, a higher speed-up in relation to a sequential implementation.

Palavras-chave: NIOS; FPGA; multiprocessors; backpropagation; pipeline; artifícial neural networks

Páginas: 3

Código DOI: 10.21528/CBRN2009-083

Artigo em PDF: 083_CBRN2009.pdf

Arquivo BibTex: 083_CBRN2009.bib