DocumentCode :
2215275
Title :
Biologically inspired image sensor/processor architecture with 2D cellular neural network for vision
Author :
Cho, Kwang-Bo ; Sheu, Bing J. ; Young, Wayne C.
Author_Institution :
Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
Volume :
1
fYear :
1998
fDate :
4-8 May 1998
Firstpage :
569
Abstract :
A scalable image sensor array processor with frame memory buffer and cellular neural network (CNN) for nearest neighbor interaction has been developed in a 0.5 μm HP CMOS technology. The CNN with analog programmable weights was constructed with compact mixed-signal VLSI circuit components in the current-mode techniques. The low voltage, low power operation is supported with the current mode scheme which scales well with the supply voltage. VLSI design of a variable gain neuron circuit can be incorporated into the prototype to realize the optimal solution capability using hardware annealing
Keywords :
CMOS analogue integrated circuits; VLSI; analogue processing circuits; cellular neural nets; image sensors; neural chips; CMOS IC; VLSI; analog programmable weights; cellular neural network; current-mode; frame memory buffer; hardware annealing; nearest neighbor interaction; scalable image sensor array processor; CMOS image sensors; CMOS process; CMOS technology; Cellular neural networks; Circuits; Image sensors; Low voltage; Nearest neighbor searches; Sensor arrays; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
ISSN :
1098-7576
Print_ISBN :
0-7803-4859-1
Type :
conf
DOI :
10.1109/IJCNN.1998.682330
Filename :
682330
Link To Document :
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