DocumentCode
2747593
Title
A nonlinear adaptive predictor for speech compression
Author
Hunt, Shawn
Author_Institution
Dept. of Electr. & Comput. Eng., Puerto Rico Univ., Mayaguez, Puerto Rico
Volume
4
fYear
1996
fDate
3-6 Jun 1996
Firstpage
1998
Abstract
A neural nonlinear predictor for one dimensional signals is presented. It is based on a combination of linearization and QR decomposition that allows a fast adapting algorithm. The predictor is used in a speech compression algorithm that has proven to be superior to linear based models. The compression and training are done simultaneously, allowing the network to continually adapt to the signal. The results presented show that this algorithm outperforms a typical LPC coding algorithm
Keywords
data compression; QR decomposition; linearization; neural nonlinear predictor; nonlinear adaptive predictor; one dimensional signals; speech compression; Bit rate; Compression algorithms; Joining processes; Linear predictive coding; Neural networks; Nonlinear equations; Predictive models; Speech coding; Stochastic resonance; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1996., IEEE International Conference on
Conference_Location
Washington, DC
Print_ISBN
0-7803-3210-5
Type
conf
DOI
10.1109/ICNN.1996.549208
Filename
549208
Link To Document