Title :
Mixed H2/ H∞ algorithm for exponentially windowed adaptive filtering
Author :
Kothari, Sandip D. ; Banavar, Ravi N. ; Chaudhuri, Subhasis
Author_Institution :
Department of Electrical Engineering, Indian Institute of Technology, Bombay, India-400076
Abstract :
The RLS or its equivalent H2 algorithms achieve the best average performance. But these suffer from poor worst case performance. Stochastic gradient based algorithms (like LMS) achieve best worst case performance, but a poor average performance. In this paper we propose switching criteria for acquiring advantages of both of these algorithms. The proposed algorithm uses a nonlinear combination of H2 optimal and H∞ optimal estimation. We present a mixed H2/H∞ algorithm employing an exponential window and the achievable bound for this estimation strategy.
Keywords :
Estimation; Robustness;
Conference_Titel :
Acoustics, Speech, and Signal Processing (ICASSP), 2002 IEEE International Conference on
Conference_Location :
Orlando, FL, USA
Print_ISBN :
0-7803-7402-9
DOI :
10.1109/ICASSP.2002.5745819