Quaternion neural networks are models in which computations of the neurons are based on
quaternions, the four-dimensional equivalents of imaginary numbers. This paper shows by …

Neural networks have attracted much interest in the last two decades for their potential to
realistically describe brain functions, but so far they have failed to provide models that can be …

Associative memory networks based on quaternionic Hopfield neural network are investigated
in this paper. These networks are composed of quaternionic neurons, and input, output, …

Electroencephalography (EEG) has long been studied as a potential diagnostic method for
Alzheimer's disease (AD). The pathological progression of AD leads to cortical disconnection…

Investigations into quantum computations have begun from the pioneering theoretical
studies of Feynman, Deutsch, and others, and detailed studies have been done since the …

In stochastic resonance (SR), the presence of noise helps a nonlinear system amplify a weak
(sub-threshold) signal. Chaotic resonance (CR) is a phenomenon similar to SR but without …

This paper explores two types of multistate Hopfield neural networks, based on commutative
quaternions that are similar to Hamilton's quaternions but with commutative multiplication. …

Quaternions are a class of hypercomplex number systems, a four-dimensional extension of
imaginary numbers, which are extensively used in various fields such as modern physics …

A quaternionic extension of feed forward neural network, for processing multi-dimensional
signals, is proposed in this paper. This neural network is based on the three layered network …

Chaotic resonance (CR), in which a system responds to a weak signal through the effects of
chaotic activities, is a known function of chaos in neural systems. The current belief suggests …