Nonlinear Analyses and Algorithms for Speech Processing: by Marcos Faundez-Zanuy, Léonard Janer, Anna Esposito, Antonio

By Marcos Faundez-Zanuy, Léonard Janer, Anna Esposito, Antonio Satue-Villar, Josep Roure, Virginia Espinosa-Duro

We found in this quantity the gathering of ?nally approved papers of NOLISP 2005 convention. it's been the 3rd occasion in a sequence of occasions regarding N- linear speech processing, within the framework of the eu price motion 277 “Nonlinear speech processing”. Many speci?cs of the speech sign should not good addressed by way of conv- tional types at present utilized in the ?eld of speech processing. the aim of NOLISP is to provide and talk about novel rules, paintings and effects with regards to substitute recommendations for speech processing, which go away from mainstream methods. With this goal in brain, we offer an open discussion board for dialogue. Alt- nate ways are liked, even if the consequences accomplished at this time would possibly not in actual fact surpass effects in accordance with cutting-edge equipment. the decision for papers was once introduced firstly of 2005, addressing the subsequent domain names: 1. Non-Linear Approximation and Estimation 2. Non-Linear Oscillators and Predictors three. Higher-Order statistics four. autonomous part research five. Nearest buddies 6. Neural Networks 7. choice timber eight. Non-Parametric versions nine. Dynamics of Non-Linear platforms 10. Fractal equipment eleven. Chaos Modeling 12. Non-Linear Di?erential Equations thirteen. Others all of the major ?elds of speech processing are certain by way of the workshop, particularly: 1. Speech Coding:Thebit rateavailablefor speechsignalsmustbe strictly l- ited on the way to accommodate the limitations of the channel resource.

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Three fuzzy sets describe the universe of discourse for the speed and previous threshold is described with 5 fuzzy sets. Triangular fuzzy sets, min-max inference and centroide defuzzification are chosen for simplicity. The aim of the rule base is to optimize the threshold depending on the terminal speed. For high speed we would like Neuro-fuzzy Logic in Signal Processing for Communications: From Bits to Protocols 33 to reduce the number of hand-offs because the terminal may go through many cells in a short time, thus the threshold should increase.

G. -J. Chang, "Design of a fuzzy traffic controller for ATM networks", IEEE Trans. Networking, Vol. 4, pp. 460-469, Jun. 1996. 17. -R. -J. Chang, "A Neural Fuzzy Resource Manager for Hierarchical Cellular Systems Supporting Multimedia Services", IEEE Trans. Veh. , Vol. 52, No. 5, pp. 1196-1206, Sep. 2003. 18. G. Edwards and R. Sankar, "Hand-off using fuzzy logic", Proc. IEEE GLOBECOM, Singapore, Vol. 1, pp. 524-528, Nov. 1995. 19. -F. -F. I. Chuang, "Fuzzy logic adaptive handoff algorithm", Proc.

Instead of resorting to statistical properties of the signals, this work treats the problem as one of image segmentation. Variants of known fuzzy classifiers are studied and compared with existing techniques, as the Unsupervised Maximum Likelihood (MLU) classifier or the watershed technique. The goal is the separation of seismic waves collected from experimental data. Whenever there is uncertainty in the statistical model, fuzzy logic can be useful. This is maybe the case of supervised classification problems when the number of training data is low, or when there is lack of knowledge in the underlying parametric model as it is the case of geophysical signals, such as the ones addressed in this paper.

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