RECURSIVE ESTIMATES OF PROBABILITY DENSITIES

被引：15

作者：

WOLVERTON, CT

WAGNER, TJ

机构：

来源：

IEEE TRANSACTIONS ON SYSTEMS SCIENCE AND CYBERNETICS | 1969年 / SSC5卷 / 03期

关键词：

D O I：

10.1109/TSSC.1969.300267

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

A pattern recognition network with two types of adaptation has been investigated. The network output is a weighted sum of the outputs of elements which compute real functions of the discrete network inputs. The first type of adaptation involves the adjustment of the weights while the second type involves the periodic replacement of the least valuable network elements with new ones. The expected error of the network in realizing arbitrary input-output functions has been found by Monte-Carlo simulation for simple weight adaptation and for the case where the population of network elements is allowed to evolve. Copyright © 1969 by The Institute of Electrical and Electronics Engineers, Inc.

引用

页码：246 / +

页数：1

共 6 条

[1]

Doob J. L., 1953, STOCHASTIC PROCESSES

[2] ON NON-PARAMETRIC ESTIMATES OF DENSITY FUNCTIONS AND REGRESSION CURVES [J].