DocumentCode :
3002535
Title :
A new compact neuron-bipolar cellular neural network structure with adjustable neighborhood layers and high integration level
Author :
Yen, Wen-Cheng ; Wu, Chung-Yu
Author_Institution :
Dept. of Electron. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Volume :
6
fYear :
1999
fDate :
36342
Firstpage :
505
Abstract :
A new compact structure called the neuron-bipolar cellular neural network is proposed and analyzed. In the new structure, the parasitic PNP bipolar junction transistor in the CMOS process is used to implement the neuron whereas the coupling MOS resistor is used to realize the synapse weights among various neurons. It has the advantages of compact structure and small chip size. The neuron-bipolar CNN with single neighborhood layer r=1 has been successfully applied to the noise removing operation on images. Moreover, the proposed neuron-bipolar CNN can easily realize the multi-layer neighborhood structure. Thus the proposed neuron-bipolar CNN has a great potential in the VLSI implementation of neural networks
Keywords :
CMOS analogue integrated circuits; VLSI; analogue processing circuits; cellular neural nets; image enhancement; image processing equipment; image reconstruction; neural chips; CMOS process; VLSI implementation; adjustable neighborhood layers; cellular neural network structure; compact neuron-bipolar CNN structure; coupling MOS resistor; high integration level; image noise removal; multilayer neighborhood structure; noise removing operation; parasitic PNP BJT; parasitic bipolar junction transistor; synapse weights; CMOS process; Cellular neural networks; Coupling circuits; Laboratories; MOSFET circuits; Neural networks; Neurons; Resistors; Semiconductor device noise; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1999. ISCAS '99. Proceedings of the 1999 IEEE International Symposium on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-5471-0
Type :
conf
DOI :
10.1109/ISCAS.1999.780205
Filename :
780205
Link To Document :
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