An Embedded Probabilistic Neural Network with On-chip Learning Capability

被引：0
|
作者：
Wang, Jen-Huo [1 ]
Tang, Kea-Tiong [1 ]
Chen, Hsin [1 ]
机构：
[1] Natl Tsing Hua Univ, Dept Elect Engn, Hsinchu 30013, Taiwan
来源：
2013 IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE (BIOCAS) | 2013年
关键词：
probabilistic neural network; CRBM; on-line learning;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：29 / 32
页数：4
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