The purpose of this section has been to introduce the reader to three examples of the ANN, and to show how the neurophysiological work on visual receptor arrays inspired their designs. By modern standards, Rosenblatt's (1958; 1962) perceptrons were the simplest of ANNs. Widrow's (1985) ADALINE and MADALINE ANNs were capable of more sophisticated pattern recognition tasks, able to generate complex decision boundaries. Fukushima (1988a) developed a series of very complex ANNs he called neocognitrons. As in the case of the earlier static feature extractors (see Section 7.1.3), Fukushima used the layered approach based on vertebrate retinal organization. While the neocognitrons performed amazing feature extraction operations, their complexity challenges most potential users, and other types of ANNs are generally used today for commercial applications.

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