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State estimation is a central problem in many engineering applications. Traditionally, Kalman filters are widely used for linear systems with additive Gaussian noise. But the many dynamic systems are much more complex, usually involve nonlinear and non-Gaussian elements. Bearing the nature of sequential importance sampling (SIS) and Monte Carlo approach, particle filtering (PF) has emerged as a superior...
The adaptive Volterra filter has been successfully applied in nonlinear acoustic echo cancellation (AEC) systems and nonlinear line echo cancellation systems, but its applications are limited by its required computational complexity and slow convergence rate, especially for systems with long memory length. In this paper, by leveraging a multi-channel configuration of the Volterra filter and the sampling...
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