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.
Original language | English |
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Title of host publication | Unknown Host Publication Title |
Publisher | IEEE |
Pages | 12-17 |
Number of pages | 6 |
ISBN (Print) | 0818608617, 9780818608612 |
DOIs | |
Publication status | Published - 1988 |
Externally published | Yes |
ASJC Scopus subject areas
- Engineering(all)