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We present a novel nonlinear echo cancellation method that assumes the Hammerstein nonlinear system model. Model parameters are identified using a neural network followed by an adaptive linear filter. The parameters of both subsystems are estimated separately, which allows the utilization of computationally efficient conventional methods. The proposed method is verified on simulated as well as on...
This paper presents a Cramér-Rao lower bound (CRLB) on the variance of unbiased estimates of factor matrices in Canonical Polyadic (CP) or CANDECOMP/PARAFAC (CP) decompositions of a tensor from noisy observations, (i.e., the tensor plus a random Gaussian i.i.d. tensor). A novel expression is derived for a bound on the mean square angular error of factors along a selected dimension of a tensor of an...
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