Elements of information theory
Elements of information theory
Elements of signal detection and estimation
Elements of signal detection and estimation
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
An error-entropy minimization algorithm for supervised training ofnonlinear adaptive systems
IEEE Transactions on Signal Processing
A low complexity robust detector in impulsive noise
Signal Processing
RKHS Bayes discriminant: a subspace constrained nonlinear feature projection for signal detection
IEEE Transactions on Neural Networks
Symmetric deformable image registration via optimization of information theoretic measures
Image and Vision Computing
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Matched filters are the optimal linear filters for signal detection under linear channel and white noise conditions. Their optimality is guaranteed in the additive white Gaussian noise channel due to the sufficiency of second-order statistics. In this paper, we introduce a nonlinear filter for signal detection based on the Cauchy-Schwartz quadratic mutual information (CS-QMI) criterion. This filter is still implementing correlation but now in a high-dimensional transformed space defined by the kernel utilized in estimating the CS-QMI. Simulations show that the nonlinear filter significantly outperforms the traditional matched filter in nonlinear channels, as expected. In the linear channel case, the proposed filter outperforms the matched filter when the received signal is corrupted by impulsive noise such as Cauchy-distributed noise, but performs at the same level in Gaussian noise. A simple nonparametric sample estimator for CS-QMI is derived for real-time implementation of the proposed filter.