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.
|Title of host publication||Unknown Host Publication Title|
|Number of pages||6|
|ISBN (Print)||0818608617, 9780818608612|
|Publication status||Published - 1988|
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