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This paper describes an improved system for obtaining velocity spectral information from electroneurogram recordings using multi-electrode cuffs (MECs). The starting point for this study is some recently published work that considers the limitations of conventional linear signal processing methods (‘delay-and-add’) with and without additive noise. By contrast to earlier linear methods, the present...
Voice activity detection (VAD) is a fundamental part of speech processing. Combination of multiple acoustic features is an effective approach to make VAD more robust against various noise conditions. There have been proposed several feature combination methods, in which weights for feature values are optimized based on minimum classification error (MCE) training. We improve these MCE-based methods...
This paper presents an approach for solving WCCI 2008's Ford Classification Challenge Problem. The solution is based on the creation of new input variables through temporal feature extraction and on the combination via bagging of an ensemble of 30 multi-layer perceptrons trained on sets divided by multiple random sampling of the labeled data. Signal power, signal to noise ratio and signal frequency...
In this paper a self tuning adaptive PID control scheme for nonlinear systems is proposed using wavelet networks. The auto tuner consists of a discrete PID controller and a proposed new wavelet network structure called dynamic wavelet network (DWN). The DWN consists of a static feedforward wavelet network in cascade with an autoregressive moving average (ARMA) model. The learning strategy for the...
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