1.
IEEE Trans Neural Netw
; 17(3): 755-70, 2006 May.
Artigo
em Inglês
| MEDLINE
| ID: mdl-16722178
RESUMO
This paper presents the VLSI implementation of the continuous restricted Boltzmann machine (CRBM), a probabilistic generative model that is able to model continuous-valued data with a simple and hardware-amenable training algorithm. The full CRBM system consists of stochastic neurons whose continuous-valued probabilistic behavior is mediated by injected noise. Integrating on-chip training circuits, the full CRBM system provides a platform for exploring computation with continuous-valued probabilistic behavior in VLSI. The VLSI CRBM's ability both to model and to regenerate continuous-valued data distributions is examined and limitations on its performance are highlighted and discussed.