Title :
QX-LMS Adaptive FIR Filters For System Identification
Author :
Guan, Xiaochun ; Chen, Xiaojing ; Wu, Guichu
Author_Institution :
Coll. of Phys. & Electron. Inf. Eng., Wenzhou Univ., Wenzhou, China
Abstract :
The least mean square (LMS) adaptive filter is popular owing to its simplicity but even simpler approaches are required for many real-time applications. Reduction of the complexity of the LMS filter had received attention in the area of adaptive filter. This paper proposes a method of system identification using adaptive filter which is based on a new quantised version of the LMS, namely the QX-LMS algorithm. The coefficients of the adaptive filter are adjusted automatically by an adaptive algorithm based on the input signals. This property makes the adaptive filter has an important application in system identification. The threshold parameter of the QX-LMS algorithm causes controllability and the increase of convergence property. The TMS320C55x is a 16-bit fixed-point DSP processor from Texas Instruments. It is designed for optimum performance and high code density. The realization of the proposed algorithm on DSP TMS320C55x is introduced and also its experiment results are discussed.
Keywords :
FIR filters; adaptive filters; computational complexity; digital signal processing chips; identification; least mean squares methods; quantisation (signal); 16-bit fixed-point DSP processor; QX-LMS adaptive FIR filter algorithm; TMS320C55x; Texas Instruments; adaptive system identification; computational complexity reduction; controllability property; convergence property; high-code density; least mean square adaptive filter; optimum performance; quantised version; real-time application; threshold parameter; Adaptive algorithm; Adaptive filters; Adaptive systems; Convergence; Digital filters; Finite impulse response filter; Least squares approximation; Signal processing; Signal processing algorithms; System identification;
Conference_Titel :
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4129-7
Electronic_ISBN :
978-1-4244-4131-0
DOI :
10.1109/CISP.2009.5301497