no code implementations • 11 Jul 2017 • Iván Castro, Cristóbal Silva, Felipe Tobar
We present a probabilistic framework for both (i) determining the initial settings of kernel adaptive filters (KAFs) and (ii) constructing fully-adaptive KAFs whereby in addition to weights and dictionaries, kernel parameters are learnt sequentially.