Title :
A neural-like network approach to residue-to-decimal conversion
Author :
Sun, Hong ; Yao, Tian-ren
Author_Institution :
Dept. of Electr. & Inf. Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
fDate :
27 Jun- 2 Jul 1994
Abstract :
In this paper, a neural-like network for computation of residue-to-decimal conversion (RDC), based on a residue reduction operation neural network we proposed, is presented. It is shown both analytically and by simulation that this RDC network is guaranteed to settle into the correct value of RDC within RC time constants, and this network is applicable for variable moduli only by alteration of its operation voltages without requiring parameters of multiplication inverses. In addition, the operation procedure of this RDC network is similar to that of human´s solving RDC problems
Keywords :
neural chips; residue number systems; neural-like network; residue reduction; residue-to-decimal conversion; Analytical models; Application software; Cathode ray tubes; Computer networks; Correlators; Neural networks; Signal processing algorithms; Sun; Very large scale integration; Voltage;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374831
