A mixed filter algorithm for cognitive state estimation from simultaneously recorded continuous and binary measures of performance

DOI10.1007/s00422-008-0227-zzbMath1158.91478OpenAlexW2103575187WikidataQ43098190 ScholiaQ43098190MaRDI QIDQ1008384

M. Yanike, W. A. Suzuki, M. J. Prerau, A. C. Smith, Uri T. Eden, Emery N. Brown

Publication date: 27 March 2009

Published in: Biological Cybernetics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc2707852

zbMATH Keywords

learningKalman filterGaussian approximationbinary filtercognitive state

Mathematics Subject Classification ID

Measurement and performance in psychology (91E45)

Related Items (2)

Discrete- and Continuous-Time Probabilistic Models and Algorithms for Inferring Neuronal UP and DOWN States ⋮ Decoding Hidden Cognitive States From Behavior and Physiology Using a Bayesian Approach

Uses Software

• astsa
• Fahrmeir

Cites Work

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• AN APPROACH TO TIME SERIES SMOOTHING AND FORECASTING USING THE EM ALGORITHM
• Protein classification by stochastic modeling and optimal filtering of amino-acid sequences
• Smoothness priors analysis of time series
• On deriving models in the social sciences
• Sequential Monte Carlo Methods in Practice
• Linear recursive state estimators under uncertain observations
• Dynamic Latent Trait Models for Multidimensional Longitudinal Data
• Estimating a State-Space Model from Point Process Observations
• Dynamic Analyses of Information Encoding in Neural Ensembles
• Dynamic Analysis of Neural Encoding by Point Process Adaptive Filtering
• Tools for statistical inference. Methods for the exploration of posterior distributions and likelihood functions.

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