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Several versions of the Daum-Huang (DH) filter have been introduced recently to address the task of discrete-time nonlinear filtering. The filters propagate a particle set over time to track the system state, but, in contrast to conventional particle filters, there is no proposal density or importance sampling involved. Particles are smoothly migrated using a particle flow derived from a log-homotopy...
This paper addresses the problem of predicting future outputs of an unknown Linear Time Invariant System based solely on past input/output data corrupted by noise, and an a-priori bound on the system order. This situation arises in many scenarios of practical interest where an explicit a-priori model of the system is not available. The main result of the paper is a simple, computationally efficient...
In this paper we address the problem of human gait recognition from a robust identification and model (in)validation prospective. The main idea is to apply dimensionality reduction technique to extract the spatio-temporal information by mapping the gait silhouette sequence to a low dimensional time sequence, which is considered as the output of a linear time invariant (LTI) system. A class of gaits...
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