EVOLUTIONAL DEVELOPMENT OF A MULTILEVEL NEURAL-NETWORK

被引：37

作者：

ODRI, SV ^{[1
]}

PETROVACKI, DP ^{[1
]}

KRSTONOSIC, GA ^{[1
]}

机构：

[1] UNIV NOVI SAD, YU-21000 NOVI SAD, YUGOSLAVIA

来源：

NEURAL NETWORKS | 1993年 / 6卷 / 04期

关键词：

NEURAL NETWORK; BACK PROPAGATION; HIDDEN CELL; EVOLUTION; CELL DIVISION; SYNAPSE; SYNAPSE DEGENERATION;

D O I：

10.1016/S0893-6080(05)80061-9

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The paper describes changes in the structure (anatomy) of a multilevel neural network which is trained by back-propagation algorithm. A structural change is both a random process and an environment-dependent process. The mechanisms of cell propagation and degeneration of inactive synapses and inactive cells are considered. The change in the neural network structure occurs during the training and running of the system, which enables dynamic adaptation of the network capacity to the complex problem of the network interaction with the environment. Structural changes in a multilevel neural network are tested on several tasks of the network training.

引用

页码：583 / 595

页数：13

共 6 条

[1] BACK-PROPAGATION ALGORITHM WHICH VARIES THE NUMBER OF HIDDEN UNITS [J].