: Following Etherington, Hoge and Parkes, we consider a network consisting of (approximately) N transceivers in the plane R2 distributed randomly with density given by a Gaussian d...
The performance of sparsely-connected associative memory models built from a set of perceptrons is investigated using different patterns of connectivity. Architectures based on Gau...
In physical implementations of associative memory, wiring costs play a significant role in shaping patterns of connectivity. In this study of sparsely-connected associative memory...
Abstract. Gaussian processes have been favourably compared to backpropagation neural networks as a tool for regression. We show that a recurrent neural network can implement exact ...
We investigate the use of an unsupervised artificial neural network to form a sparse representation of the underlying causes in a data set. By using fixed lateral connections that...