An embedded probabilistic neural network with on-chip learning capability

Jen-Huo Wang; Kea-Tiong Tang; Hsin Chen

doi:10.1109/BioCAS.2013.6679632

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Conference paper

An embedded probabilistic neural network with on-chip learning capability

Jen-Huo Wang, Kea-Tiong Tang and Hsin Chen

2013 IEEE Biomedical Circuits and Systems Conference, BioCAS 2013, pp.29-32

2013

DOI: https://doi.org/10.1109/BioCAS.2013.6679632

Abstract

CRBM

on-line learning

probabilistic neural network

An embedded system capable of recognizing biomedical signals reliably is important for fusing sensory data of portable or implantable microsystems in biomedical applications. This paper presents the digital VLSI implementation of the probabilistic neural network, called the Continuous Restricted Boltzmann Machine (CRBM), which is able to cluster or to classify sensory data of an electronic nose. The learning algorithm of the CRBM is also realized on the same chip, such that the CRBM system is able to optimize its parameters automatically, or to compensate for sensory drifts by on-line learning. © 2013 IEEE.

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Title: An embedded probabilistic neural network with on-chip learning capability
Creators - without role: Jen-Huo Wang - National Tsing Hua University
Kea-Tiong Tang - Department of Electrical Engineering , National Tsing Hua University
Hsin Chen - National Tsing Hua University
Publication Details: 2013 IEEE Biomedical Circuits and Systems Conference, BioCAS 2013, pp.29-32
Identifiers: 9781479914715; 9957774810106774
Academic Unit: Department of Electrical Engineering, College of Electrical Engineering and Computer Science, National Tsing Hua University; Institute of Electronics Engineering, College of Electrical Engineering and Computer Science, National Tsing Hua University
Language: English
Resource Type: Conference paper

An embedded probabilistic neural network with on-chip learning capability

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