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Current-Mode Computation with Noise in a Scalable and Programmable Probabilistic Neural VLSI System

  • Chih-Cheng Lu
  • H. Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5768)

Abstract

This paper presents the VLSI implementation of a scalable and programmable Continuous Restricted Boltzmann Machine (CRBM), a probabilistic model proved useful for recognising biomedical data. Each single-chip system contains 10 stochastic neurons and 25 adaptable connections. The scalability allows the network size to be expanded by interconnecting multiple chips, and the programmability allows all parameters to be set and refreshed to optimum values. In addition, current-mode computation is employed to increase dynamic ranges of signals, and a noise generator is included to induce continous-valued stochasticity on chip. The circuit design and corresponding measurement results are described and discussed.

Keywords

Probabilistic VLSI noise scalable and programmable systems 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Chih-Cheng Lu
    • 1
  • H. Chen
    • 1
  1. 1.The Dept. of Electrical EngineeringThe National Tsing-Hua UniversityHsin-ChuTaiwan

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