
This Article  
 
Share  
Bibliographic References  
Add to:  
Digg Furl Spurl Blink Simpy Del.icio.us Y!MyWeb  
Search  
 
ASCII Text  x  
Zheng Tang, Qiping Cao, Okihiko Ishizuka, "A Learning MultipleValued Logic Network: Algebra, Algorithm, and Applications," IEEE Transactions on Computers, vol. 47, no. 2, pp. 247251, February, 1998.  
BibTex  x  
@article{ 10.1109/12.663773, author = {Zheng Tang and Qiping Cao and Okihiko Ishizuka}, title = {A Learning MultipleValued Logic Network: Algebra, Algorithm, and Applications}, journal ={IEEE Transactions on Computers}, volume = {47}, number = {2}, issn = {00189340}, year = {1998}, pages = {247251}, doi = {http://doi.ieeecomputersociety.org/10.1109/12.663773}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Computers TI  A Learning MultipleValued Logic Network: Algebra, Algorithm, and Applications IS  2 SN  00189340 SP247 EP251 EPD  247251 A1  Zheng Tang, A1  Qiping Cao, A1  Okihiko Ishizuka, PY  1998 KW  Multiplevalued logic KW  learning capability KW  functional completeness KW  backpropagation algorithm. VL  47 JA  IEEE Transactions on Computers ER   
Abstract—We propose a multiplevalued logic (MVL) network with functional completeness and develop its learning capability. The MVL network consists of layered arithmetic piecewise linear processors. Since the arithmetic operations of the network are basically a wiredsum and a piecewise linear operation, their implementations should be rather simple and straightforward. Furthermore, the MVL network can be trained by the traditional backpropagation algorithm directly. The algorithm trains the networks using examples and appears to be available for most MVL problems of interest.
[1] G. Epstein, G. Frieder, and D.C. Rine, "The Development of MultipleValued Logic as Related to Computer Science," Computer, vol. 7, pp. 2032, 1974.
[2] K.C. Smith, "The Prospects for Multivalued Logic: A Technology and Application View," IEEE Trans. Computers, vol. 30, pp. 619634, 1981.
[3] S.L. Hurst, "MultipleValued Logic—Its Status and Its Future," IEEE Trans. Computers, vol. 33, no. 12, pp. 1,1601,179, Dec. 1984.
[4] M. Kameyama, T. Hanyu, and T. Higuchi, "Design and Implementation of Quaternary NMOS Integrated Circuits for PipeLine Image Processing," IEEE J. SolidState Circuits, vol. 12, no. 1, pp. 2027, 1987.
[5] K.C. Smith, "A MultipleValued Logic: A Tutorial and Appreciation," Computer, vol. 21, no. 4, pp. 1727, Apr. 1988.
[6] J.J. Hopfield and D.W. Tank, "Simple Neural Optimization Networks: An A/D Converter, Signal Decision Circuit, and a Linear Programming Circuit," IEEE Trans. Circuits and Systems, vol. 33, pp. 533541, May 1986.
[7] Z. Tang, O. Ishizuka, and H. Matsumoto, "Implementing Nerual Architecture Using CMOS CurrentMode VLSI Circuits," IEICE Trans. Fundamentals, vol. 74, no. 5, pp. 1,3291,336, May 1991.
[8] Z. Tang, O. Ishizuka, and H. Matsumoto, "MultipleValued NeuroAlgebra," IEICE Trans. Fundamentals, vol. 76A, no. 9, pp. 1,5411,543, Sept. 1993.
[9] H.R. Berenji and P. Khedkar, "Learning and Training Fuzzy Logic Controllers Through Reinforcements," IEEE Trans. Neural Networks, vol. 3, no. 5, pp. 724740, 1992.
[10] R. Rosenblatt, Principles of Neurodynamics.New York: Spartan Book, 1959.
[11] A. Kramer and A. SangiovanniVincentelli, "Efficient Parallel Learning Algorithm for Neural Networks," Advances in Neural Information Systems, vol. 1, pp. 4048.San Mateo, Calif.: Morgan Kaufmann, 1989.