An assembly neural network for texture segmentation

An architecture of a neural network with assembly organization is described. Such network architecture is applied to the problem of texture segmentation bn natural scenes. The network is partitioned into several sub-networks. Each subnetwork is a column structure in which features me represented by means of ''float'' coding. Input data excite corresponding ''floats'' of neurons in the subnetworks. In the process of learning the weights of modifiable connections between excited neurons are changed so that Hebb's assemblies are formed in the column structures. All subnetworks me incorporated into a single network by a neural activity control system. Computer simulation of the proposed network has been performed. The results of computer simulations show the possibility of successful application of the assembly neural network to the problem of texture segmentation. Copyright (C) 1996 Elsevier Science Ltd