Title :
An optimized automatic gain controller for real time recursive LMS adaptive filters
Author :
Tapia, Javier ; Kuo, Sen M.
Author_Institution :
Dept. of Electr. Eng., Northern Illinois Univ., De Kalb, IL, USA
Abstract :
An optimized automatic gain controller (AGC) to improve the performance of a recursive least mean squares (LMS) adaptive filter for an active noise control application is designed and implemented. The gain is self-adjusted over a broad range (40 dB), and considerable changes in amplitude produced by electromechanical resonances can be controlled for the adaptive infinite impulse response (IIR) filter. Experiments of noise attenuation system show that the behavior of the recursive LMS adaptive filter with this optimized AGC is improved in terms of stability and convergence rate during a frequency sweep in an acoustic duct. The controller allows the attenuation of strong signals. An input test signal with abrupt changes of 10 dB at each step (from 0 to 40 dB) is made, and it is controlled without changes in the performance of the recursive LMS filter
Keywords :
adaptive filters; automatic gain control; convergence; digital filters; filtering and prediction theory; least squares approximations; real-time systems; stability; LMS adaptive filters; acoustic duct; active noise control application; adaptive IIR filter; automatic gain controller; convergence rate; electromechanical resonances; frequency sweep; infinite impulse response; least mean squares; optimized AGC; real time recursive filter; stability; Active noise reduction; Adaptive filters; Attenuation; Automatic control; Design optimization; IIR filters; Least squares approximation; Performance gain; Programmable control; Resonance;
Conference_Titel :
Circuits and Systems, 1990., IEEE International Symposium on
Conference_Location :
New Orleans, LA
DOI :
10.1109/ISCAS.1990.112681
