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An iterative approach to identification of a quadratic Volterra system with noisy input-output is proposed, whereby the bias-compensated least-squares method of identifying a noisy FIR model is utilised with some modification to estimate input/output noise variances and bias-removed Volterra system parameters. In particular, the proposed identification approach yields better performance even in cases...
Variable-to-check residual belief propagation for LDPC decoding for faster convergence, better error performance and lower complexity is proposed. It is similar to residual belief propagation (RBP) that was recently applied to LDPC decoding by Vila Casado etal. because it is also a dynamic scheduling belief propagation using residuals, but it is different because the residuals are computed from a...
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