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