We propose an integrated framework for the design of SOC test solutions, which includes a set of algorithms for early design space exploration as well as extensive optimization for...
This article introduces the idea that information compression by multiple alignment, unification and search (ICMAUS) provides a framework within which natural language syntax may ...
The learned parametric mixture method is presented for a canonical cost function based ICA model on linear mixture, with several new findings. First, its adaptive algorithm is fu...
This work addresses the problem of finding the adjustable parameters of a learning algorithm using Genetic Algorithms. This problem is also known as the model selection problem. In...
We derive solutions for the problem of missing and noisy data in nonlinear timeseries prediction from a probabilistic point of view. We discuss different approximations to the so...