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Jonathan R. Potts

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Open access Aug 2026

Behavioural state identification from ultra‐high‐frequency movement data

This study introduces a fast and accurate method for identifying animal behavioural states from high‐frequency data (e.g. ≥1 Hz) within the HMM framework and develops a new HMM model for identifying behavioural states that accounts for steps that are of differing durations.

Abdulmajeed F. Alharbi, P. G. Blackwell, James Redcliffe et al. · 0 citations

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