Whereas a signijcant attzount of empirical work has been carried out in the area of logical neural networks, the fundamental theoretical basis is underdeveloped. This paper provides an analysis of recurrent nets of a$ne Boolean functions and defines the relation between their behaviour and that of linear Boolean nets. It is shown that the only effect on the unlabelled state structure of adding any number of inverters to a linear Boolean net is a restricted modification of cycle lengths.
This paper discusses the areas of investigation required to develop synthesis techniques for Boolean Neural Networks. Consideration is given to the problems of behavioural specification and to the lack of an analytic algebraic mapping between transformations within the hyper-state space and transformations within the function space of a network Ways of identifying structure within both the behaviour and functional architecture of classes of simple Boolean Neural Networks are suggested.
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