The importance of bringing causality into play when designing feature selection methods is more and more acknowledged in the machine learning community. This paper proposes a filt...
We present an Abstract Interpretation-based framework for automatically analyzing programs containing digital filters. Our framework allows refining existing analyses so that the...
Existing systolic architectures for the LMS algorithm with delayed coeficient adaptation have large adaptation delay and hence degraded convergence behaviour. This paper presents ...
Most existing approaches for single-channel noise reduction in the frequency domain via the short-time Fourier transform (STFT) assume that consecutive time-frames are uncorrelate...
We describe a recommender system which uses a unique combination of content-based and collaborative methods to suggest items of interest to users, and also to learn and exploit it...