Artificial Neural Systems: Principle and Practice

Basic Fuzzy Neuron and Fundamentals of ANN

Author(s): Pierre Lorrentz

Pp: 28-39 (12)

DOI: 10.2174/9781681080901115010005

* (Excluding Mailing and Handling)


The chapter’s aim and objectives are to provide an artificial neural-based fuzzy-logic foundation, and a general framework for design and analysis of ANN systems. The first section therefore introduces membership functions, define and give a relatively full operational description of fuzzy-logic neuron. Subsequent section two introduces ANN design principles and analysis from which a general wave neural network is derived. A full understanding of this chapter may be sufficient to design and analyse any artificial neural network system.

Keywords: Aggregation operator, Bell-shaped, Composite, Delta-function, Experience, Fuzzy-set, Fuzziness, Gaussian, Hessian, Lower bound, Lagrange, Membership grade, Operator, Peak, Relation, Stimuli, Support set, Upper bound.

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