Multivariate Shannon's entropy for adaptive IIR filtering via kernel density estimators - Fantinato, D.G; Silva, D.G; Attux, R; Neves, A (Electronics letters, 2019)
Keywords: adaptive filters; adaptive IIR; approximate gradient‐based approaches; entropy; equalisers; filtering theory; gradient methods; higher order statistics; IIR filters; information theoretic learning criterion; kernel density estimators; learning (artificial intelligence); mean square error methods; mean squared error criterion; MSE; multivariate entropy definition; noisy scenarios; optimisation; optimisation methods; Recursive Prediction Error‐based algorithm; Shannon's entropy; Shannon's error entropy; Signal processing; supervised channel equalisation problem; supervised infinite impulse response adaptive filtering; underlying signals; usual option; mean squared error criterion; IIR filters; kernel density estimators; Shannon's error entropy; multivariate entropy definition; optimisation; entropy; adaptive IIR; supervised infinite impulse response adaptive filtering; Recursive Prediction Error-based algorithm; equalisers; learning (artificial intelligence); mean square error methods; gradient methods; noisy scenarios; MSE; approximate gradient-based approaches; adaptive filters; optimisation methods; filtering theory; information theoretic learning criterion; higher order statistics; usual option; underlying signals; Shannon's entropy; supervised channel equalisation problem