Title :
Multinomial conjunctoid statistical learning machines
Author :
Takefuji, Y. ; Jannarone, R. ; Cho, Y.B. ; Chen, Tatung
Author_Institution :
Dept. of Electr. & Comput. Eng., South Carolina Univ., Columbia, SC, USA
fDate :
30 May-2 Jun 1988
Abstract :
A statistical learning model called the multinomial conjunctoid is reviewed. Multinomial conjunctoids are based on a well-developed, statistical-decision-theory framework, which guarantees that conjunctoid learning will converge to optimal states over learning trials and the learning will be fast during these trials. In addition, a prototype multinomial conjunctoid module based on CMOS VLSI technology is introduced
Keywords :
CMOS integrated circuits; VLSI; computer architecture; learning systems; neural nets; CMOS VLSI technology; multinomial conjunctoid; statistical learning model; statistical-decision-theory framework; Artificial neural networks; CMOS technology; Convergence; Decision theory; Integrated circuit interconnections; Machine intelligence; Neural networks; Neurons; Prototypes; Semiconductor device modeling; Statistical learning; Very large scale integration;
Conference_Titel :
Computer Architecture, 1988. Conference Proceedings. 15th Annual International Symposium on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-8186-0861-7
DOI :
10.1109/ISCA.1988.5205
