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Found 4 papers, 1 papers with code
An Analytic Solution for Kernel Adaptive Filtering
We provide an extended functional Wiener equation, and present a solution to this equation in an explicit, finite dimensional, data-dependent RKHS.
An Alternate View on Optimal Filtering in an RKHS
Kernel Adaptive Filtering (KAF) are mathematically principled methods which search for a function in a Reproducing Kernel Hilbert Space.
The Functional Wiener Filter
Because of the lack of congruence between the Gaussian RKHS and the space of time series, we compare performance of two pre-imaging algorithms: a fixed-point optimization (FWFFP) that finds and approximate solution in the RKHS, and a local model implementation named FWFLM.
SignalTrain: Profiling Audio Compressors with Deep Neural Networks
In this work we present a data-driven approach for predicting the behavior of (i. e., profiling) a given non-linear audio signal processing effect (henceforth "audio effect").
