S. Luttrell

发表

The use of transinformation in the design of data sampling schemes for inverse problems

S. Luttrell, 1985 .

Bayesian Methods for Adaptive Models

Peter Cheeseman, Radford M. Neal, Haim Sompolinsky, 2011 .

Hierarchical self-organising networks

S. P. Luttrell, S. Luttrell, 1989 .

Derivation of a Class of Training

S. Luttrell, 1990 .

Self-supervised adaptive networks

S. P. Luttrell, S. Luttrell, 1992 .

A Bayesian Analysis of Self-Organizing Maps

S. P. Luttrell, S. Luttrell, 1994, Neural Computation.

An adaptive Bayesian network for low-level image processing

S. P. Luttrell, S. Luttrell, 1993 .

A trainable texture anomaly detector using the Adaptive Cluster Expansion (ACE) method

S. Luttrell, Radar Establishment, 1990 .

A super-resolution algorithm for SAR images

S. P. Luttrell, G. C. Pryde, L M Delves, 1988 .

The inverse cross section problem for complex data

S. Luttrell, 1989 .

Network Analysis Techniques

Russell Beale, Alexander Linden, Stephen Luttrell, 1996 .

The Wilson coefficient functions of four-quark operators and the four-quark process in deep inelastic scattering

S. Luttrell, B. Webber, S. Wada, 1981 .

A Bayesian derivation of an iterative autofocus/super-resolution algorithm

S. P. Luttrell, S. Luttrell, 1990 .

Ultra High-resolution imaging assembly

S. Luttrell, C. Oliver, 1985 .

Prior Knowledge and Object Reconstruction Using the Best Linear Estimate Technique

S. P. Luttrell, S. Luttrell, 1985 .

The current product expansion of the two-quark process at the twist-four level

S. Luttrell, S. Wada, 1982 .

Heavy quark production in electromagnetic deep inelastic scattering and QCD analysis of isosinglet moments

S. Luttrell, S. Wada, 1981 .

The use of Markov random field models to derive sampling schemes for inverse texture problems

S P Luttrell, S. Luttrell, 1987 .

The theory of Bayesian super-resolution of coherent images: a review

S. P. Luttrell, S. Luttrell, 1991 .

Adaptive Bayesian networks

S. P. Luttrell, S. Luttrell, 1992, Defense, Security, and Sensing.

The Use of Bayesian and Entropic Methods in Neural Network Theory

S. P. Luttrell, S. Luttrell, 1989 .

The Use Of Markov Random Field Models In Sampling Scheme Design

S. P. Luttrell, S. Luttrell, 1987, Other Conferences.

An optimisation of the Metropolis algorithm for multibit Markov random fields

S. Luttrell, 1986 .

The role of prior knowledge in coherent image processing

S. P. Luttrell, C. J. Oliver, S. Luttrell, 1988, Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences.

Bayesian autofocus/super-resolution theory

S. P. Luttrell, S. Luttrell, 1990 .

Self-organisation: a derivation from first principles of a class of learning algorithms

S. P. Luttrell, S. Luttrell, 1989, International 1989 Joint Conference on Neural Networks.

Derivation of a class of training algorithms

Stephen P. Luttrell, S. Luttrell, 1990, IEEE Trans. Neural Networks.

A Markov Chain Approach to Multiple Classifier Fusion

Stephen P. Luttrell, S. Luttrell, 2003, Multiple Classifier Systems.

Hierarchical vector quantisation

S. P. Luttrell, S. Luttrell, 1989 .