1.
IEEE Trans Neural Netw
; 6(3): 767-70, 1995.
Artigo
em Inglês
| MEDLINE
| ID: mdl-18263362
RESUMO
In this paper we give a formal definition of the high-order Boltzmann machine (BM), and extend the well-known results on the convergence of the learning algorithm of the two-order BM. From the Bahadur-Lazarsfeld expansion we characterize the probability distribution learned by the high order BM. Likewise a criterion is given to establish the topology of the BM depending on the significant correlations of the particular probability distribution to be learned.