1,165 research outputs found

    Studies in Signal Processing Techniques for Speech Enhancement: A comparative study

    Get PDF
    Speech enhancement is very essential to suppress the background noise and to increase speech intelligibility and reduce fatigue in hearing. There exist many simple speech enhancement algorithms like spectral subtraction to complex algorithms like Bayesian Magnitude estimators based on Minimum Mean Square Error (MMSE) and its variants. A continuous research is going and new algorithms are emerging to enhance speech signal recorded in the background of environment such as industries, vehicles and aircraft cockpit. In aviation industries speech enhancement plays a vital role to bring crucial information from pilot’s conversation in case of an incident or accident by suppressing engine and other cockpit instrument noises. In this work proposed is a new approach to speech enhancement making use harmonic wavelet transform and Bayesian estimators. The performance indicators, SNR and listening confirms to the fact that newly modified algorithms using harmonic wavelet transform indeed show better results than currently existing methods. Further, the Harmonic Wavelet Transform is computationally efficient and simple to implement due to its inbuilt decimation-interpolation operations compared to those of filter-bank approach to realize sub-bands

    Demagnetization via Nucleation of the Nonequilibrium Metastable Phase in a Model of Disorder

    Full text link
    We study both analytically and numerically metastability and nucleation in a two-dimensional nonequilibrium Ising ferromagnet. Canonical equilibrium is dynamically impeded by a weak random perturbation which models homogeneous disorder of undetermined source. We present a simple theoretical description, in perfect agreement with Monte Carlo simulations, assuming that the decay of the nonequilibrium metastable state is due, as in equilibrium, to the competition between the surface and the bulk. This suggests one to accept a nonequilibrium "free-energy" at a mesoscopic/cluster level, and it ensues a nonequilibrium "surface tension" with some peculiar low-T behavior. We illustrate the occurrence of intriguing nonequilibrium phenomena, including: (i) Noise-enhanced stabilization of nonequilibrium metastable states; (ii) reentrance of the limit of metastability under strong nonequilibrium conditions; and (iii) resonant propagation of domain walls. The cooperative behavior of our system may also be understood in terms of a Langevin equation with additive and multiplicative noises. We also studied metastability in the case of open boundaries as it may correspond to a magnetic nanoparticle. We then observe burst-like relaxation at low T, triggered by the additional surface randomness, with scale-free avalanches which closely resemble the type of relaxation reported for many complex systems. We show that this results from the superposition of many demagnetization events, each with a well- defined scale which is determined by the curvature of the domain wall at which it originates. This is an example of (apparent) scale invariance in a nonequilibrium setting which is not to be associated with any familiar kind of criticality.Comment: 26 pages, 22 figure

    Optimum and suboptimum array processing for the estimation of superimposed signals

    Get PDF
    Bibliography: p. 46-47.Supported in part by the Army Research Office. DAAG29-84-K-0005 Supported in part by the Army Research Office. DAAL03-86-K-1071 Supported in part by the National Science Foundation. ECS-8312921by Anthony J. Weiss, Alan S. Willsky, Bernard C. Levy

    Superselectors: Efficient Constructions and Applications

    Full text link
    We introduce a new combinatorial structure: the superselector. We show that superselectors subsume several important combinatorial structures used in the past few years to solve problems in group testing, compressed sensing, multi-channel conflict resolution and data security. We prove close upper and lower bounds on the size of superselectors and we provide efficient algorithms for their constructions. Albeit our bounds are very general, when they are instantiated on the combinatorial structures that are particular cases of superselectors (e.g., (p,k,n)-selectors, (d,\ell)-list-disjunct matrices, MUT_k(r)-families, FUT(k, a)-families, etc.) they match the best known bounds in terms of size of the structures (the relevant parameter in the applications). For appropriate values of parameters, our results also provide the first efficient deterministic algorithms for the construction of such structures
    corecore