Construct The Structure of Stochastic Multilayer Perceptron Using The Model Search Method.pdf

Construct The Structure of Sto chastic Multilayer Perceptron Using The Mo del Search Metho d Shiro IKEDA The Institute of Physical and Chemical Research RIKEN Abstract ones by adding some new parameters to the mo del The author gives an algorithm to search the struc Thus the machine searches the optimal structure of the mo del ture of a sto chastic mo dels with hidden variable The author have shown the algorithm to nd the hidden In this article the author gives the outline of the al structure of the Hidden Markov Mo del and in this gorithm and simple exp eriment which is applied for article the algorithm is applied for one of the other probabilistic Neural Networks sto chastic multilayer sto chastic mo dels which have hidden probabilistic vari Perceptron which was prop osed by Amari In the ables sto chastic multilayer Perceptron each cell b ehaves in sto chastic manner and the cells in hidden layer are the I Introduction hidden probabilistic variables For these probabilistic mo del we can use EM Exp ectation Maximization The Neural Networks have great ability to express var ious typ es of functions The Neural Network has this algorithm to estimate the parameters And in this article the EM algorithm acts the imp ortant role for ability b ecause it has a lot of parameters and also b e searching the mo del structure The