학술논문

Analog addition/subtraction on the CNN-UM chip with short-time superimposition of input signals
Document Type
Periodical
Source
IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications IEEE Trans. Circuits Syst. I Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on. 50(3):429-432 Mar, 2003
Subject
Components, Circuits, Devices and Systems
Cellular neural networks
Signal processing algorithms
Equivalent circuits
Feedback circuits
Cloning
Image processing
Signal processing
Voltage
Capacitors
Object detection
Language
ISSN
1057-7122
1558-1268
Abstract
The cellular-neural-network universal machine (CNN-UM) technique which performs analog addition/subtraction between image frames has been developed. The equivalent circuit of the uncoupled CNN without self feedback is reduced to a simple RC circuit. If two inputs are presented to the circuit one after another during a very short time period, the voltages that are proportional to their input signals are superimposed on the state capacitor. The output of such superimposition is a reduced version of the addition/subtraction between the two signals. Simple amplification of the output can recover the actual output. The characteristics of analog addition/subtraction with the proposed algorithm are shown via on-chip experiment. Application of the proposed algorithm to moving target detection is also presented.