ANALYSIS AND IMPROVEMENT OF RECURRENT CORRELATION NEURAL NETWORKS

Zhang Yongjun; Chen Zongzhi

Volume 18 Issue 6

Nov. 1996

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Article Navigation > Journal of Electronics & Information Technology > 1996 > 18(6): 596-600

Jiaao YU, Shirui PENG, Xiaokun CHEN, Youquan LI. Equivalent Circuit Method for Hexagonal Loop Composite Absorbing Material[J]. Journal of Electronics & Information Technology, 2018, 40(8): 1873-1878. doi: 10.11999/JEIT171103

Citation:

Zhang Yongjun, Chen Zongzhi. ANALYSIS AND IMPROVEMENT OF RECURRENT CORRELATION NEURAL NETWORKS[J]. Journal of Electronics & Information Technology, 1996, 18(6): 596-600.

Citation:

Zhang Yongjun, Chen Zongzhi. ANALYSIS AND IMPROVEMENT OF RECURRENT CORRELATION NEURAL NETWORKS[J]. Journal of Electronics & Information Technology, 1996, 18(6): 596-600.

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ANALYSIS AND IMPROVEMENT OF RECURRENT CORRELATION NEURAL NETWORKS

Zhang Yongjun^{①;陈宗骘},
Chen Zongzhi

Received Date: 1994-12-08
Rev Recd Date: 1995-04-13
Publish Date: 1996-11-19

Abstract

Abstract

This paper analyzes the relationship between capacity and dynamics in recurrent correlation neural network, and points out that in some conditions the recurrent correlation neural network has high memory capacity. Then this paper presents several methods for improving the performance.

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References(1)

References

McEliece J R. IEEE Trans. on IT, 1987, IT-33(4): 461-482.[2]Chiueh Tzi-Dar. IEEE Trans. on NN，1991, NN-2(2): 275-284.[3]Zhang Yongjun, Chen Zongzhi. Recurrent Correlation Neural Network loop. IJCNN92, Vo1.2 Beijing: 1992, 109-114.

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