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http://dx.doi.org/10.3745/KIPSTB.2002.9B.4.429

Analysis of the Effect on the Quantization of the Network's Outputs in the Neural Processor by the Implementation of Hybrid VLSI  

Kwon, Oh-Jun (Dongeui University)
Kim, Seong-Woo (Dongeui University)
Lee, Jong-Min (Dongeui University)
Publication Information
The KIPS Transactions:PartB / v.9B, no.4, 2002 , pp. 429-436 More about this Journal
Abstract
In order to apply the artificial neural network to the practical application, it is needed to implement it with the hardware system. It is most promising to make it with the hybrid VLSI among various possible technologies. When we Implement a trained network into the hybrid neuro-chips, it is to be performed the process of the quantization on its neuron outputs and its weights. Unfortunately this process cause the network's outputs to be distorted from the original trained outputs. In this paper we analysed in detail the statistical characteristics of the distortion. The analysis implies that the network is to be trained using the normalized input patterns and finally into the solution with the small weights to reduce the distortion of the network's outputs. We performed the experiment on an application in the time series prediction area to investigate the effectiveness of the results of the analysis. The experiment showed that the network by our method has more smaller distortion compared with the regular network.
Keywords
Neuro-chip; Hardware; Distortion of the network's outputs;
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