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This paper proposes a new classifier scheme based on classical clustering algorithms, such as the Batchelor & Wilkins y K-means algorithms which are trained in a similar form that the artificial neural network (ANN) or support vector machines (SVM). Proposed scheme has the advantage that if a new class is added, it is not necessary to train he classifier completely, but only add a new class. Experimental...
Atomic functions are widely used to solve problems of numerical analysis since they are high accurate and present some interesting computational properties. These functions can be applied to construct weighting windows for digital signal processing, for this reason, in this work we present an implementation on a digital signal processor to compare the characteristics of the filters designed with classical...
In this paper, a DSP-Based of an oversampling adaptive noise canceller for background noise reduction using the Recursive Least Squares (RLS) algorithm on a Digital Signal Processor (DSP) is presented and its performance discussed. The implementation described seeks to improve the signal to background noise ratio for effective telephone communication in adverse non-stationary acoustic environments...
This paper proposes a Speech Recognition Application (SRA) for speech recognition with an accuracy location of endpoints on a speech signal-recording, with an Adaptive Equalization (AE), Energy Pulse Detector (EPD), Feature Extraction (FE) and a decision rule Database MySQL. In order to localize an endpoint in the signal, a signal recording has been processed by the Endpoint Detector Algorithm (EDA)...
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