1 citations · 2 across the 13 of their papers we have counts for
13 papers
Some Theoretical Properties of a Network of Discretely Firing Neurons
Stephen Luttrell
The problem of optimising a network of discretely firing neurons is addressed. An objective function is introduced which measures the average number of bits that are needed for the…
A Self-Organising Neural Network for Processing Data from Multiple Sensors
S P Luttrell
This paper shows how a folded Markov chain network can be applied to the problem of processing data from multiple sensors, with an emphasis on the special case of 2 sensors. It is…
Self-Organising Stochastic Encoders
Stephen Luttrell
The processing of mega-dimensional data, such as images, scales linearly with image size only if fixed size processing windows are used. It would be very useful to be able to autom…
The Development of Dominance Stripes and Orientation Maps in a Self-Organising Visual Cortex Network (VICON)
Stephen Luttrell
A self-organising neural network is presented that is based on a rigorous Bayesian analysis of the information contained in individual neural firing events. This leads to a visual…
Stochastic Vector Quantisers
Stephen Luttrell
In this paper a stochastic generalisation of the standard Linde-Buzo-Gray (LBG) approach to vector quantiser (VQ) design is presented, in which the encoder is implemented as the sa…
Adaptive Cluster Expansion (ACE): A Multilayer Network for Estimating Probability Density Functions
Stephen Luttrell
We derive an adaptive hierarchical method of estimating high dimensional probability density functions. We call this method of density estimation the "adaptive cluster expansion" o…