|2/2006 - 7|
Noisy Voice Pattern Recognition by Three-Rate Hybrid Neural NetworkIgor ASTROV, Svetlana TATARLY, Sergei TATARLY
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Simulation, multi-rate, neural networks, voice pattern, pattern recognition
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About this article
Date of Publication: 2006-10-02
Volume 6, Issue 2, Year 2006, On page(s): 35 - 38
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: Not assigned
This paper presents the three-rate hybrid neural network (TRHNN) for processing of noisy signal. The received TRHNN consists of /fast/ back-propagation neural network (FBPNN), /intermediate/ back-propagation neural network (IBPNN) and /slow/ Kohonen neural network (SKNN). The illustrative example - recognition and restoration of noisy voice pattern - was carried out using the TRHNN. The received TRHNN has not only high speed of signal processing, but also high speed of signal restoration. This example demonstrates that the proposed TRHNN is capable not only to identify the noisy input pattern, but also to restore the noise-free input pattern. The simulation results with use the software package Simulink show the computing procedure and applicability of TRHNNs for fast-acting signal processing and analysis in real-time conditions.
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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