Title :
Analog CMOS implementation of cellular neural networks
Author :
Baktir, Izzet Adil ; Tan, Mehmet Ali
Author_Institution :
Dept. of Electr. & Electron. Eng., Bilkent Univ., Ankara, Turkey
fDate :
3/1/1993 12:00:00 AM
Abstract :
The analog CMOS circuit realization of cellular neural networks with transconductance elements is presented. This realization can be easily adapted to various types of applications in image processing just by choosing the appropriate transconductance parameters according to the predetermined coefficients. The effectiveness of the designed circuits for connected component detection is shown by HSPICE simulations. For fixed function cellular neural network circuits, the number of transistors is reduced further by using multi-input transconductance elements
Keywords :
CMOS integrated circuits; SPICE; analogue processing circuits; circuit analysis computing; neural chips; HSPICE simulations; analog CMOS circuit realization; cellular neural networks; connected component detection; multi-input transconductance elements; predetermined coefficients; transconductance elements; Artificial neural networks; Biological neural networks; CMOS analog integrated circuits; Cellular neural networks; Image processing; Parallel processing; Transconductance; Transducers; Very large scale integration; Voltage;
Journal_Title :
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on
