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NIPS
2003

Minimising Contrastive Divergence in Noisy, Mixed-mode VLSI Neurons

9 years 5 months ago
Minimising Contrastive Divergence in Noisy, Mixed-mode VLSI Neurons
This paper presents VLSI circuits with continuous-valued probabilistic behaviour realized by injecting noise into each computing unit(neuron). Interconnecting the noisy neurons forms a Continuous Restricted Boltzmann Machine (CRBM), which has shown promising performance in modelling and classifying noisy biomedical data. The Minimising-Contrastive-Divergence learning algorithm for CRBM is also implemented in mixed-mode VLSI, to adapt the noisy neurons’ parameters on-chip.
Hsin Chen, Patrice Fleury, Alan F. Murray
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2003
Where NIPS
Authors Hsin Chen, Patrice Fleury, Alan F. Murray
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