Complex-valued neural networks Complex-Valued Neural Networks Page 2 IEEE Press 445
Hoes Lane Piscataway, NJ 08854 IEEE Press Editorial Board 2013 John Anderson, Editor in …

The use of complex numbers in neural networks is as natural as their use in other
engineering areas and in mathematics. The history of complex numbers shows that although …

In many studies, it is common to use binary (ie, unweighted) edges to examine networks of
entities that are either adjacent or not adjacent. Researchers have generalized such binary …

Complex fuzzy sets (CFSs) are an extension of type-1 fuzzy sets in which the membership of
an object to the set is a value from the unit disc of the complex plane. Although there has …

Complex fuzzy sets utilize a complex degree of membership, represented in polar
coordinates, which is a combination of a degree of membership in a fuzzy set along with a …

Applications of complex-valued neural networks to optical signal processing using phase-
sensitive detection schemes are proposed and discussed. In optical information processing …

In recent years, several neural networks using Clifford algebra have been studied. Clifford
algebra is also called geometric algebra. Complex-valued Hopfield neural networks …

In this paper, we address the stability of a broad class of discrete-time hypercomplex-valued
Hopfield-type neural networks. To ensure the neural networks belonging to this class always …

Complex fuzzy sets, classes, and logic have an important role in applications, such as
prediction of periodic events and advanced control systems, where several fuzzy variables …

In recent years, there has been a rapid expansion in the field of nonlinear optics as weIl as
in the field of neural computing. Up to date, no one would doubt that nonlinear optics is one …