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 …

Information coding by precise timing of spikes can be faster and more energy efficient than
traditional rate coding. However, spike-timing codes are often brittle, which has limited their …

Neural dynamical systems with stable attractor structures, such as point attractors and
continuous attractors, are hypothesized to underlie meaningful temporal behavior that …

Multidirectional associative memory neural network (MAMNN) is a direct extension of
bidirectional associative memory neural network, which can handle multiple associations. In …

In this paper, a fully complex-valued radial basis function (FC-RBF) network with a fully
complex-valued activation function has been proposed, and its complex-valued gradient …

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

Recently models of neural networks that can directly deal with complex numbers, complex-
valued neural networks, have been proposed and several studies on their abilities of …

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 …

Visual odometry (VO) is a method used to estimate self-motion of a mobile robot using visual
sensors. Unlike odometry based on integrating differential measurements that can …