In this paper we introduce a simple and mathematically tractable model of an asynchronous
spiking neural network which to some extent generalizes the concept of a Boltzmann …

In recent two decades neuroscience and computational intelligence has experienced a
large progress, with some new important concepts being developed like spiking (Bohte …

We investigate sparse networks of threshold units, trained with the perceptron learning rule
to act as associative memories. The units have position and are placed in a ring so that the …

Using probabilistic approach, the transient dynamics of sparsely connected Hopfield neural
networks is studied for arbitrary degree distributions. A recursive scheme is developed to …

The performance of a locally-connected associative memories built from a onedimensional
array of perceptrons with a fixed number of afferent connections per unit is investigated …

The performance of sparsely-connected associative memory models built from a set of
perceptrons is investigated using different patterns of connectivity. Architectures based on …

By using the generalized Chua's chaotic oscillator as fundamental unit, a complex network
displaying the small-world property is synchronized. Authors resort to existing information …

Autoassociative fuzzy implicative memories (AFIMs) are models that exhibit optimal absolute
storage capacity and an excellent tolerance with respect to incomplete or eroded patterns …

This study examines the performance of sparsely-connected associative memory models
built using a number of different connection strategies, applied to one-and two-dimensional …

Associative Memories with Small World Connectivity Page 1 74 Associative Memories with Small
World Connectivity Neil Davey, Lee Calcraft, Bruce Christianson, Rod Adams Department of …