The Adaptive γ-LMS Filtering Algorithm for Time Delay Estimation

• Main Authors: Ko, Chih Hsun, 柯志勳
• Other Authors: Chern, Shiunn Jang
• Format: Others
• Language: en_US
• Published: 1996
• Online Access: http://ndltd.ncl.edu.tw/handle/93714737827987160589

碩士 === 國立中山大學 === 電機工程研究所 === 84 === The main concerns of this thesis is to improve the performance of non-integer time delay estimation by the so-call adaptive γ-LMS algorithm. When noise is present, in an adaptive TDE system, the FIR weight coefficients may not converge to the correct values, resulting in TDE performance degradation. To speed up The convergence rate of the tap-weight coefficients, an adaptive γ-LMS algorithm is presented. After the weight coefficients are obtained the direct delay estimation formula is employed for non- integer time delay estimation. Computer simulation results verified the adaptive γ-LMS algorithm over the conventional adaptive LMS algorithm in term of non-integer time delay estimation. Moreover, to examine the steady- state property, the steady-state mean weight vector and the sum of the mean squared weight errors, the weight-error variance of the γ-LMS algorithm are derived. Another topic which will be considered in this thesis is the variable step- size, The convergence rate of the ada- ptive filtering algorithm is proportional to step-size, and generally, the misadjustment value is inversely pro- portional to step- size. The proper choice of the step- size is the key to assure good performance. The variable step size of the adaptive γ-LMS is desgined to reduce the squared estimation error and to speed up the conver- gence rate.