Inhibitory connections in the assembly neural network for texture segmentation

被引:7
|
作者
Goltsev, A
Wunsch, DC
机构
[1] Ukrainian Acad Sci, Cybernet Ctr, UA-252650 Kiev, Ukraine
[2] Texas Tech Univ, Dept Elect Engn, Appl Computat Intelligence Lab, Lubbock, TX 79409 USA
关键词
connection matrix; excitatory connections; inhibitory connections; negative features; neural assemblies; neurons; subnetworks; texture segmentation;
D O I
10.1016/S0893-6080(98)00053-7
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A neural network with assembly organization is described. This assembly network is applied to the problem of texture segmentation in natural scenes. The network is partitioned into several subnetworks: one for each texture class. Hebb's assemblies are formed in the subnetworks during the process of training the excitatory connections. Also, a structure of the inhibitory connections is formed in the assembly network during a separate training process. The inhibitory connections result in inhibitory interactions between different subnetworks. Computer simulation of the network has been performed. Experiments show that an adequately trained assembly network with inhibitory connections is more efficient than without them. (C) 1998 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:951 / 962
页数:12
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