We propose to use the Gamma filter [1] as a feature extractor for the preprocessing of speech signals. Gamma filter which can be implemented as a cascade of identical first order lowpass filters generates at its taps the Poisson Moments of an input signal. These moments carry spectral information about the recent history of the input signal. They can be used to construct time-frequency represen...

Audio-visual documents obtained from German TV news are classified according to the IPTC topic categorization scheme. To this end usual text classification techniques are adapted to speech, video, and non-speech audio. For each of the three modalities word analogues are generated: sequences of syllables for speech, “video words” based on low level color features (color moments, color correlogra...

Fourier spectral method can achieve exponential accuracy both on the approximation level and for sQIving partial differential equations if the solutions are analytic. For a linear PDE with discontinuous solutions, Fourier spectral method will produce poor point-wise accuracy without post-processing, but still maintains exponential accuracy for all moments against analytic functions. In this not...

A new method for doing text-independent speaker identification geared to forensic situations is presented. By analysing ‘isolexemic’ sequences, the method addresses the issues of very short criminal exemplars and the need for open-set identification. An algorithm is given that computes an average spectral shape of the speech to be analysed for each glottal pulse period. Each such spectrum is co...

Relationships between ergodicity and structures of fourthorder spectral moments are investigated. In particular it is shown that second-order ergodicity of a random process is directly related to the distribution of these moments on the normal manifolds of the frequency domain. This result is illustrated by various examples.

Abstract: We study some connections between the random moment problem and the random matrix theory. A uniform pick in a space of moments can be lifted into the spectral probability measure of the pair (A, e) where A is a random matrix from a classical ensemble and e is a fixed unit vector. This random measure is a weighted sampling among the eigenvalues of A. We also study the large deviations ...

We consider N×N Hermitian or symmetric random matrices with independent entries. The distribution of the (i, j)-th matrix element is given by a probability measure νij whose first two moments coincide with those of the corresponding Gaussian ensemble. We prove that the joint probability distribution of the components of eigenvectors associated with eigenvalues close to the spectral edge agrees ...

This paper describes a classification method for rotated and scaled textured images using invariant parameters based on spectral-moments. Although it is well known that rotation invariants can be derived from moments of grey-level images, the use is limited to binary images because of its computational unstableness. In order to obtain computationally stable moments, we use power spectrum instea...

We present a model order reduction method which allows the construction of a reduced, delay free model of a given dimension for linear time-delay systems, whose characteristic matrix is nonlinear due to the presence of exponential functions. The method builds on the equivalent representation of the time-delay system as an infinite-dimensional linear problem. It combines ideas from a finite-dime...

Abstract: We consider asymptotic problems in spectral analysis of stationary causal processes. Limiting distributions of periodograms and smoothed periodogram spectral density estimates are obtained and applications to spectral domain bootstrap are made. Instead of the commonly used strong mixing conditions, in our asymptotic spectral theory we impose conditions only involving (conditional) mom...