Blind adaptive channel equalization using multichannel linear prediction-based cross-correlation vector estimation

2004 ◽  
Vol 50 (4) ◽  
pp. 1026-1032 ◽  
Author(s):  
Kyung Seung Ahn ◽  
Juphil Cho ◽  
Heung Ki Baik
2005 ◽  
Vol 83 (7) ◽  
pp. 721-737
Author(s):  
H Teffahi ◽  
B Guerin ◽  
A Djeradi

Knowledge of vocal tract area functions is important for the understanding of phenomena occurring during speech production. We present here a new measurement method based on the external excitation of the vocal tract with a known pseudo-random sequence, where the area function is obtained by a linear prediction analysis applied to the cross-correlation between the sequence and the signal measured at the lips. The advantages of this method over methods based on sweep-tones or white noise excitation are (1) a much shorter measurement time (about 100 ms) and (2) the possibility of speech sound production during the measurement. This method has been checked against classical methods through systematic comparisons on a small corpus of vowels. Moreover, it has been verified that simultaneous speech sound production does not perturb significantly the measurements. This method should thus be a very helpful tool for the investigation of the acoustic properties of the vocal tract in various cases for vowels.


2013 ◽  
Vol 658 ◽  
pp. 537-540
Author(s):  
Sun Shouyu

The constant modulus algorithm (CMA) equalizer is perhaps the best known and the most popular scheme for blind adaptive channel equalization. In this paper, a modified constant modulus algorithm (modified CMA or MCMA) is proposed by modifying its error function. We have discussed the MCMA to blind channel equalization for baud-rat sampling in single-user case. Computer simulations are provided for 8PSK signals in noise environments under frequency selective channels. Results demonstrate that the MCMA displays much superior performance to the CMA for both convergence-time and intersymbol interference (ISI) or mean square error (MSE).


Sign in / Sign up

Export Citation Format

Share Document