Estimating divergence between two point processes, i.e. probability laws on the space of spike trains, is an essential tool in many computational neuroscience applications, such a...
In this work a new online learning algorithm that uses automatic relevance determination (ARD) is proposed for fast adaptive nonlinear filtering. A sequential decision rule for i...
Thomas Buchgraber, Dmitriy Shutin, H. Vincent Poor
Parallel computation of the adaptive lattice filtering algorithm is difficult due to the dependency problem caused by feedback operations. The conventional control-level paralle...
It is well known that LDPC decoding is computationally demanding and one of the hardest signal operations to parallelize. Beyond data dependencies that restrict the decoding of a ...
In many applications non-stationary Gaussian or stationary nonGaussian noises can be observed. In this paper we present a maximum a posteriori estimation jointly of spectral ampli...