Title :
An introduction to conjunctoid theory and architecture
Author :
Lii ; Ma, Kwan-Liu ; Wei, Xiuqin
Abstract :
Summary form only given, as follows. The main early results from conjunctoid learning theory are reviewed. Recent conjunctoid results are outlined, including: (1) a new formulation that treats supervised and unsupervised learning-as well as reinforced learning, associative memory and optimization-as special cases; (2) advances in conditional maximum-likelihood estimation toward consistent, noniterative, and highly parallel learning trial updating; (3) advances in VLSI implementation and Monte-Carlo simulation; and (4) the resulting applications prospects.<>
Keywords :
learning systems; neural nets; parallel architectures; Monte-Carlo simulation; VLSI implementation; associative memory; conjunctoid learning theory; maximum-likelihood estimation; neural nets; parallel learning; reinforced learning; supervised learning; unsupervised learning; Learning systems; Neural networks; Parallel architectures;
Conference_Titel :
Neural Networks, 1989. IJCNN., International Joint Conference on
Conference_Location :
Washington, DC, USA
DOI :
10.1109/IJCNN.1989.118522
