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
Código DOI: 10.21528/CBRN2009-083
Artigo em PDF: 083_CBRN2009.pdf
Arquivo BibTex: 083_CBRN2009.bib