Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Neural-Network-Based Time-Delay Estimation Samir Shaltaf | EURASIP Journal on Applied Signal Processing 2004 3 378-385 2004 Hindawi Publishing Corporation Neural-Network-Based Time-Delay Estimation Samir Shaltaf Department of Electronic Engineering Princess Sumaya University for Technology . Box 1438 Al-Jubaiha 11941 Amman Jordan Email shaltaf@ Received 4 May 2003 Revised 13 August 2003 Recommended for Publication by John Sorensen A novel approach for estimating constant time delay through the use of neural networks NN is introduced. A desired reference signal and a delayed damped and noisy replica of it are both filtered by a fourth-order digital infinite impulse response IIR filter. The filtered signals are normalized with respect to the highest values they achieve and then applied as input for an NN system. The output of the NN is the estimated time delay. The network is first trained with one thousand training data set in which each data set corresponds to a randomly chosen constant time delay. The estimated time delay obtained by the NN is an accurate estimate of the exact time-delay values. Even in the case of noisy data the estimation error obtained was a fraction of the sampling time interval. The delay estimates obtained by the NN are comparable to the estimated delay values obtained by the cross-correlation technique. The main advantage of using this technique is that accurate estimation of time delay results from performing one pass of the filtered and normalized data through the NN. This estimation process is fast when compared to the classical techniques utilized for time-delay estimation. Classical techniques rely on generating the computationally demanding cross-correlation function of the two signals. Then a peak detector algorithm is utilized to find the time at which the peak occurs. Keywords and phrases Neural networks time-delay estimation. 1. INTRODUCTION Time-delay estimation problem has received considerable attention because of its diverse applications. Some of its applications exist .
