MULTIPLIERLESS MULTILAYER FEEDFORWARD NEURAL-NETWORK DESIGN SUITABLE FOR CONTINUOUS INPUT-OUTPUT MAPPING

被引:9
作者
KWAN, HK
TANG, CZ
机构
[1] Department of Electrical Engineering, University of Windsor, Windsor, Ontario N9B 3P4
关键词
NEURAL NETWORKS;
D O I
10.1049/el:19930841
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A method for designing a multiplierless multilayer feed-forward neural network (MFNN) suitable for continuous input-output mapping is presented. When tested with noisy vectors, the network can retain a similar recall accuracy as the corresponding MFNN with continuous weights. The advantages of the design method include faster computational speed and reduced digital hardware cost.
引用
收藏
页码:1259 / 1260
页数:2
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