By Topic

Neural-based smart CMOS sensors for on-line pattern classification applications

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Djahanshahi, H. ; Dept. of Electr. Eng., Windsor Univ., Ont., Canada ; Jullien, G.A. ; Miller, W.C. ; Ahmadi, M.

We review previous work on CMOS photoreceptors and neural-based smart sensors that are VLSI realization of a neural network classifier with an integrated photoreceptor array. These sensors are designed for on-line pattern classification applications requiring image capture or non-contact measurement. Photoreceptors are based on Field-Effect-Modified parasitic phototransistors in CMOS technology. Several designs have been implemented. A pre-programmed smart photosensor fabricated in 3 μ CMOS has been successfully tested and a programmable version has been fabricated in 1.2 μ. The latest design of smart sensor is based on a novel unified synapse-neuron building block that results in a highly modular, scalable and area-efficient VLSI architecture. A test circuit containing an 8×8 photosensitive array and a fully-connected programmable neural network with N=54 inputs, m=8 hidden neurons and k=4 output neurons has been designed in the 1.2 μ technology. Based on the new architecture synaptic density has been doubled, and we have been able to increase the size of the optical input array as well as neural classifier itself

Published in:

Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on  (Volume:4 )

Date of Conference:

12-15 May 1996