In prior work, the current authors investigated the use of optimization criteria for beamforming that exploit the non-Gaussianity of human speech. In particular, we examined beamforming algorithms designed to maximize the kurtosis or negentropy of the subband output of a generalized sidelobe canceller. These techniques, while effective, require making multiple passes through the data, and hence...

The problem of measuring the disparity of a particular probability density function from a normal one has been addressed in several recent studies. The most used technique to deal with the problem has been exact expressions using information measures over particular distributions. In this paper, we consider a class of asymmetric distributions with a normal kernel, called Generalized Skew-Normal...

An extension of the infomax algorithm of Bell & Sejnowski (1995) is presented that is able to separate the mixed suband super-Gaussian source distributions. The same learning rule has been derived by Giiolami & Fyfe (1997) from the negentropy perspective for projection pursuit. Using a Laplacian prior we also propose a learning rule that is especially convenient to realize in hardware. The natu...

MOTIVATION The huge growth in gene expression data calls for the implementation of automatic tools for data processing and interpretation. RESULTS We present a new and comprehensive machine learning data mining framework consisting in a non-linear PCA neural network for feature extraction, and probabilistic principal surfaces combined with an agglomerative approach based on Negentropy aimed a...

The study of the rate and rate constants in the alcoholysis of n-caproyl chloride in acetone and acetonitrile, reveals that SN2 mechanism is more favourable than SN1. A plot of logarithm of rate constant against the logarithm of molar concentration of alcohol gives a straight line with a slope close to 1.1 and that with respect to water is 1.5 both in acetone and acetonitrile. This shows that i...

A block-iterative projection algorithm for solving the consistent convex feasibility problem in a finite-dimensional Euclidean space that is resilient to bounded and summable perturbations (in the sense that convergence to a feasible point is retained even if such perturbations are introduced in each iterative step of the algorithm) is proposed. This resilience can be used to steer the iterativ...

Expressions are given for a solvent dynamics-modified Rice–Ramsperger–Kassel–Marcus ~RRKM! theory for clusters. The role of vibrational assistance across the transition state region is included. The usual differential equation for motion along the slow coordinate X in constant temperature systems is modified so as to apply to microcanonical systems. A negative entropy term, 2Sv(X), replaces the...

3 TGD based variant of Beauregard’s model and generalization of thermodynamics 3 3.1 Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 3.2 What happens in quantum jump? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 3.3 Modification of thermodynamics to take into account negentropic entanglement . . . . 4 3.4 The analog of Carnot cy...

The present paper is written as a word of caution, with users of independent component analysis (ICA) in mind, to overlearning phenomena that are often observed. We consider two types of overlearning, typical to high-order statistics based ICA. These algorithms can be seen to maximise the negentropy of the source estimates. The first kind of overlearning results in the generation of spike-like ...