The Emergence of Structured Receptive Fields in a Constructive Neural Network Model

this paper is structured as follows: in the following section, I will introduce constructive network algorithms, reviewing considerations of performance and problems of conventional networks and the solutions offered in constructive architectures on the one side, and introducing the new paradigm of constructivism on the other side, outlining the learning theoretical and psychological reasons which make constructive algorithms interesting within that new theoretical framework. In Section 3, I will begin with a brief sketch of the mammalian visual system and the specific structural properties that have been found in it. I will then examine the self-organising models presented by Willshaw and von der Malsburg (1976) and Linsker (1986a,b,c). Of these, the model by Willshaw and von der Malsburg will prove constructivist. Consequently, Section 4 will provide an attempt to extend the Linsker model in a constructivist way as well as the attempt to reproduce in this new architecture some of the remarkable results Linsker had achieved. It will also briefly consider the properties of the extended Linsker algorithm with regard to feature extraction. 2 CONSTRUCTIVE NETWORK ALGORITHMS 2 2 Constructive Network Algorithm