Dr Nigel Newton
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Email
njn@essex.ac.uk -
Location
1NW.4.20, Colchester Campus
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Academic support hours
P/T
Profile
Biography
Member of the Communication Networks Research Group (See also:staff research interests by category)
Research and professional activities
Research interests
Numerical methods for stochastic processes with application to signal processing, control engineering, economics and physics
Nonlinear filtering and stochastic control
Statistical methods in telecommunications
Information Theory and Information Geometry
I am interested in connections between information theory and statistical mechanics; in particular in the way information flows between interacting systems. This has strong connections with nonlinear filtering and stochastic control. Information geometry provides a natural framework in which to set many of these ideas.
Conferences and presentations
Nonparametric Information Geometry
Invited presentation, London, United Kingdom, 6/2018
Information Geometric Nonlinear Filtering: a Hilbert Space Approach
Invited presentation, Liblice Castle, Prague, Czechia, 6/2016
An Information Geometric Representation for Nonlinear Filters
Invited presentation, ICMS, Edinburg, United Kingdom, 9/2015
Teaching and supervision
Current teaching responsibilities
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Mathematics for Computing (CE141)
Publications
Journal articles (26)
Newton, NJ., A Class of Non-Parametric Statistical Manifolds modelled on Sobolev Space
Newton, NJ., Transfer Entropy and Directed Information in Gaussian diffusion processes
Newton, NJ., (2018). Manifolds of Differentiable Densities. ESAIM: Probability and Statistics. 22, 19-34
Newton, NJ., (2016). Infinite-dimensional statistical manifolds based on a balanced chart. Bernoulli. 22 (2), 711-731
Newton, NJ., (2015). Information geometric nonlinear filtering. Infinite Dimensional Analysis, Quantum Probability and Related Topics. 18 (02), creators-Newton=3ANigel_J=3A=3A
Newton, NJ., (2015). Information geometric nonlinear filtering. Infinite Dimensional Analysis, Quantum Probability and Related Topics. 18 (02), 1550014-1550014
Sandberg, H., Delvenne, J., Newton, NJ. and Mitter, SK., (2014). Maximum work extraction and implementation costs for nonequilibrium Maxwell's demons. Physical Review E. 90 (4), creators-Newton=3ANigel_J=3A=3A
Sandberg, H., Delvenne, J-C., Newton, NJ. and Mitter, SK., (2014). Maximum work extraction and implementation costs for nonequilibrium Maxwell's demons. Physical Review E. 90 (4), 042119-
Newton, NJ. and Mitter, SK., (2012). Variational Bayes and a problem of reliable communication: II. Infinite systems. Journal of Statistical Mechanics: Theory and Experiment. 2012 (11), creators-Newton=3ANigel_J=3A=3A
Newton, NJ., (2012). An infinite-dimensional statistical manifold modelled on Hilbert space. Journal of Functional Analysis. 263 (6), 1661-1681
Newton, NJ. and Mitter, SK., (2012). Variational Bayes and a problem of reliable communication: II. Infinite systems. Journal of Statistical Mechanics: Theory and Experiment. 2012 (11), P11008-P11008
Newton, NJ. and Mitter, SK., (2010). Variational Bayes and a Problem of Reliable Communication I: Finite Systems. Communications in Information and Systems. 10 (3), 155-182
Newton, NJ., (2008). Interactive Statistical Mechanics and Nonlinear Filtering. Journal of Statistical Physics. 133 (4), 711-737
Newton, NJ., (2007). Dual Nonlinear Filters and Entropy Production. SIAM Journal on Control and Optimization. 46 (5), 1637-1663
Newton, NJ., (2006). Dual Kalman–Bucy Filters and Interactive Entropy Production. SIAM Journal on Control and Optimization. 45 (3), 998-1016
Mitter, SK. and Newton, NJ., (2005). Information and Entropy Flow in the Kalman?Bucy Filter. Journal of Statistical Physics. 118 (1-2), 145-176
Mitter, SK. and Newton, NJ., (2003). A Variational Approach to Nonlinear Estimation. SIAM Journal on Control and Optimization. 42 (5), 1813-1833
Newton, NJ., (2002). Data synchronization and noisy environments. IEEE Transactions on Information Theory. 48 (8), 2253-2262
Newton, NJ., (2001). Approximations for Nonlinear Filters based on Quantisation. Monte Carlo Methods and Applications. 7 (3-4), 311-320
Newton, NJ., (2000). Observation sampling and quantisation for continuous-time estimators. Stochastic Processes and their Applications. 87 (2), 311-337
Newton, NJ., (2000). Observations Preprocessing and Quantization for Nonlinear Filters. SIAM Journal on Control and Optimization. 38 (2), 482-502
Newton, NJ. and Schill, DW., (1996). Nonlinear methods for frame alignment. Electronics Letters. 32 (6), 523-523
Newton, NJ., (1994). Variance Reduction for Simulated Diffusions. SIAM Journal on Applied Mathematics. 54 (6), 1780-1805
Newton, NJ., (1991). Asymptotically Efficient Runge-Kutta Methods for a Class of Itô and Stratonovich Equations. SIAM Journal on Applied Mathematics. 51 (2), 542-567
Newton, NJ., (1990). An efficient approximation for stochastic differential equations on the partition of symmetrical first-passage times. Stochastics and Stochastics Reports. 29 (2), 227-258
Newton, NJ., (1986). An asymptotically efficient difference formula for solving stochastic differential equations. Stochastics. 19 (3), 175-206
Book chapters (3)
Newton, NJ., (2011). Dual filters, path estimators and information. In: The Oxford Handbook of Nonlinear Filtering. Editors: Crisan, D. and Rosovskii, B., . OUP Oxford. 471- 499. 0199532907. 9780199532902
Newton, NJ., (1997). Continuous-time Monte-Carlo methods and variance reduction. In: Numerical Methods in Finance. Editors: Rogers, LCG. and Talay, D., . Cambridge University Press. 22- 42. 0521573548. 9780521573542
Newton, NJ., (1993). Making digital decisions. In: Digital transmission. Editors: Jones, E., . McGraw-Hill Companies. 0077078101. 9780077078102
Conferences (7)
Newton, N. and Mitter, SK., A statistical mechanical view of nonlinear filtering
Newton, N., (2018). Nonlinear filtering and information geometry: A hilbert manifold approach
Sandberg, H., Delvenne, J-C., Newton, NJ. and Mitter, SK., (2014). Thermodynamic costs in implementing Kalman-Bucy filters
Newton, NJ., (2013). Infinite-Dimensional Manifolds of Finite-Entropy Probability Measures
Newton, NJ., (1996). Variance reduced Monte Carlo methods for PDEs
(1996). Numerical methods for stochastic differential equations
Newton, NJ., (1986). Asymptotically Optimal Discrete Approximations for Stochastic Differential Equations.
Contact
Academic support hours:
P/T