DocumentCode
1917859
Title
An analog silicon retina with multi-chip configuration
Author
Kameda, Seiji ; Yagi, Tetsuya
Author_Institution
Dept. of Electron. Eng., Osaka Univ., Japan
Volume
1
fYear
2003
fDate
20-24 July 2003
Firstpage
387
Abstract
The neuromorphic silicon retina is a novel analog very large scale integrated (VLSI) circuit that emulates the structure and the function of the retinal neuronal circuit. We fabricated a neuromorphic silicon retina in which sample/hold circuits were embedded to generate fluctuation-suppressed outputs in the previous study. This silicon retina, however, has a trade-off problem between the resolution and the computational complexity as the neuromorphic silicon retina generally does, since the photo sensors and processing circuits are fabricated on a single-ship. To solve the problem, we have designed a multi-chip silicon retina in which the functional network circuits are divided into two chips, the photoreceptor network chip (P chip) and the horizontal cell network chip (H chip). The output images of the chips are transferred to the H chip with analog voltages through line-parallel transfer bus. The sample/hold circuits embedded in the H chip compensate for the pattern noise generated on the transfer pathway. The number of pixels and the fill factor increased three times and twice as much as the previously fabricated chip, respectively.
Keywords
CMOS analogue integrated circuits; CMOS image sensors; VLSI; computational complexity; eye; neural chips; neurophysiology; physiological models; VLSI; analog silicon retina; analog very large scale integrated; computational complexity; fill factor; fluctuation-suppressed outputs; horizontal cell network chip; multichip configuration; neuromorphic silicon retina; photo sensors; photoreceptor network chip; pixels; processing circuits; resolution; retinal neuronal circuit; Circuits; Computational complexity; Neuromorphics; Neurons; Photoreceptors; Retina; Signal processing; Silicon; Very large scale integration; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2003. Proceedings of the International Joint Conference on
ISSN
1098-7576
Print_ISBN
0-7803-7898-9
Type
conf
DOI
10.1109/IJCNN.2003.1223377
Filename
1223377
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