6 papers · 1 filter
Generative Modeling for Physiological Signals
Xinqi Bao, Ernest Kamavuako, Saikat Chatterjee
Physiological signals support clinical diagnosis, health monitoring, rehabilitation, wearable sensing, and human--machine interaction. However, their applications are often constra…
Diffusion-Based Heart Sound Generation: Evaluation with Physiological Signal Metrics, Classifiers, and Expert Listening
Xinqi Bao, Jia Bi, Xin Chen +2
Publicly available phonocardiogram (PCG) datasets remain limited in size and pathological diversity, constraining both auscultation training and the generalisation of automated hea…
Semi-Supervised Model-Free Bayesian State Estimation from Compressed Measurements
Anubhab Ghosh, Yonina C. Eldar, Saikat Chatterjee
We consider data-driven Bayesian state estimation from compressed measurements (BSCM) of a model-free process. The dimension of the temporal measurement vector is lower than that o…
pDANSE: Particle-based Data-driven Nonlinear State Estimation from Nonlinear Measurements
Anubhab Ghosh, Yonina C. Eldar, Saikat Chatterjee
We consider the problem of designing a data-driven nonlinear state estimation (DANSE) method that uses (noisy) nonlinear measurements of a process whose underlying state transition…
DNS: Data-driven Nonlinear Smoother for Complex Model-free Process
Fredrik Cumlin, Anubhab Ghosh, Saikat Chatterjee
We propose data-driven nonlinear smoother (DNS) to estimate a hidden state sequence of a complex dynamical process from a noisy, linear measurement sequence. The dynamical process…
VSE: Variational state estimation of complex model-free process
Gustav Norén, Anubhab Ghosh, Fredrik Cumlin +1
We design a variational state estimation (VSE) method that provides a closed-form Gaussian posterior of an underlying complex dynamical process from (noisy) nonlinear measurements.…