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This paper introduces new ideas on wideband stationary/non-stationary noise removal for audio signals. Current noise reduction techniques have generally proven to be effective, yet these typically exhibit certain undesirable characteristics. Distortion and/or alteration of the audio characteristics of primary audio sound is a common problem. Also user intervention in identifying the noise profile is sometimes necessary. The proposed technique is centered on the classical Kalman filtering technique for noise removal but uses a novel architecture whereby advanced signal processing techniques are used to identify and preserve the richness of the audio spectrum. The paper also includes conceptual and derivative results on parameter estimation, a description of multi parameter Signal Activity Detector (SAD) and our new found improved results.

Abstract
Declarative systems, such as logic programming, should be ideal to process large data sets efficiently. Unfortunately, the high-level nature of logic-based representations can cause inefficiencies, and may lead in some cases to unacceptable performance. We discuss how logic programming systems can accommodate large amounts of data in main memory. We use a number of real datasets to evaluate performance and discuss how a number of techniques can be used to improve memory scalabality for such datasets.

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We present an architecture that allows the seamless configuration of computer labs to work as dedicated computing clusters during periods of user inactivity. The operation of the cluster is fully automated by making use of differentiated network booting and a job management system. We have prepared it to be plugged to a larger computational grid. We provide some preliminary performance results obtained.

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This chapter presents EPSO (Evolutionary Particle Swarm Optimization), as an evolutionary meta-heuristic that implements a scheme of self-adaptive recombination, borrowing the movement rule from PSO (Particle Swarm Optimization). Besides the basic model, it discusses a Stochastic Star topology for the communication among particles and presents a variant called differential EPSO or dEPSO. The chapter presents results in a didactic Unit Commitment/Generator Scheduling Power System problem and results of a competition among algorithms in an intelligent agent platform for Energy Retail Market simulation where EPSO comes out as the winner algorithm. © 2007 Springer-Verlag Berlin Heidelberg.

Abstract