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An Algorithm for Approximating the Second Moment of the Normalizing Constant Estimate from a Particle Filter

We propose a new algorithm for approximating the non-asymptotic second moment of the marginal likelihood estimate, or normalizing constant, provided by a particle filter. The computational cost of the new method is O(M) per time step, independently of the number of particles N in the particle filter, where M is a parameter controlling the quality of the approximation. This is in ...

A hidden Markov model for decoding and the analysis of replay in spike trains

Centre for Complexity Sciences, University of Bristol , Bristol , UK 1 Matt W. Jones 2 Nick Whiteley 3 School of Mathematics, University of Bristol , Bristol , UK 4 School of Physiology and Pharmacology