DocumentCode :
296035
Title :
Pitch synchronous Fourier transform using neural networks
Author :
Namba, Munehiro ; Ishida, Yoshihisa
Author_Institution :
Dept. of Electron. & Commun., Meiji Univ., Kawasaki, Japan
Volume :
5
fYear :
1995
fDate :
Nov/Dec 1995
Firstpage :
2896
Abstract :
In this paper, we present an overall view of the adaptive discrete Fourier transform algorithm using neural networks, and its application example for adaptive filtering. The underlying concept of the proposed method is that the continuous Fourier transform can be approximated by the discrete Fourier transform. For structuring an inverse transform system, Fourier coefficients corresponding to weight values in the network are obtained by the backpropagation algorithm to minimize the error between the output of neural networks and the signals to be analyzed. Simulation results show that our method is effective and useful for the spectral analysis of the speech signals
Keywords :
backpropagation; discrete Fourier transforms; neural nets; spectral analysis; speech processing; synchronisation; Fourier coefficients; adaptive discrete Fourier transform; backpropagation; inverse transform system; neural networks; pitch synchronous Fourier transform; spectral analysis; speech signals; weight values; Adaptive filters; Algorithm design and analysis; Analytical models; Backpropagation algorithms; Discrete Fourier transforms; Filtering algorithms; Fourier transforms; Neural networks; Signal analysis; Spectral analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
Type :
conf
DOI :
10.1109/ICNN.1995.488195
Filename :
488195
Link To Document :
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