Ensemble hidden Markov models for biosignal analysis by Rezek, I, Roberts, S

Coupled hidden Markov models for biosignal interaction modelling by Rezek, I, Sykacek, P, Roberts, S, IEE, IEE

Learning interaction dynamics with coupled hidden Markov models by Rezek, I, Sykacek, P, Roberts, S

“…Interactions between such signals can be modelled in state space rather than observation space, i.e. interactions are modelled after first translating the observations into a common domain. Coupled hidden Markov models (CHMM) are such state-space models. …”

Maximum a Posteriori Estimation of Coupled Hidden Markov Models. by Rezek, I, Gibbs, M, Roberts, S

“…Coupled Hidden Markov Models (CHMM) are a tool which model interactions between variables in state space rather than observation space. …”

Estimation of Coupled Hidden Markov Models with application to biosignal interaction modelling by Rezek, I, Roberts, S

Dynamic state allocation for MEG source reconstruction. by Woolrich, M, Baker, A, Luckhoo, H, Mohseni, H, Barnes, G, Brookes, M, Rezek, I

“…The method is underpinned by a Hidden Markov Model (HMM), which infers the points in time when particular states re-occur in the sensor space data. …”

Positional entropy during pigeon homing I: application of Bayesian latent state modelling. by Roberts, S, Guilford, T, Rezek, I, Biro, D

“…We analyse a fundamental measure of bird flight track complexity, spatio-temporal entropy, and explore its state-like structure using a probabilistic hidden Markov model. The emergence of a robust three-state structure proves that the technique has analytical power, since this structure was not obvious in the tracks alone. …”

Positional entropy during pigeon homing II: navigational interpretation of Bayesian latent state models. by Guilford, T, Roberts, S, Biro, D, Rezek, I

“…We analyse a fundamental measure of bird flight track complexity, spatio-temporal entropy, and explore its state-like structure using a probabilistic hidden Markov model. The emergence of a robust three-state structure proves that the technique has analytical power, since this structure was not obvious in the tracks alone. …”