Introduces novel zero-phase filter matrix designs and three new sparsity-assisted models (SASD, SAPR, SASDPR) that combine LTI filters, sparse derivatives, and wavelets for simultaneous denoising and pattern recognition, demonstrated on sleep EEG.
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Bayesian particle filtering with Rao-Blackwellisation for joint kinematic state and latent intent estimation using virtual leader models on simulated and radar data.
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Sparsity-Assisted Signal Denoising and Pattern Recognition in Time-Series Data
Introduces novel zero-phase filter matrix designs and three new sparsity-assisted models (SASD, SAPR, SASDPR) that combine LTI filters, sparse derivatives, and wavelets for simultaneous denoising and pattern recognition, demonstrated on sleep EEG.
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Joint Object Tracking and Intent Recognition
Bayesian particle filtering with Rao-Blackwellisation for joint kinematic state and latent intent estimation using virtual leader models on simulated and radar data.