Title :
Study of nonlinear variants of the least mean square (LMS) algorithm
Author :
Van Saders, J.G. ; Bar-Ness, Y.
Author_Institution :
New Jersey Inst. of Technol., Newark, NJ, USA
Abstract :
The class of LMS-type algorithms utilizing zero-memory limiters (on one or both correlation multiplier inputs) is examined. A theorem by R. Price (1958) is utilized to simplify the analysis, which otherwise might be extremely difficult. The correlator limiters may be included to simplify the hardware implementation or may arise owing to the effect of limited dynamic range in the loop components. The analysis provides closed-form expressions for the mean weight convergence behavior, permitting establishment of convergence and performance bounds for this class of algorithms
Keywords :
adaptive filters; filtering and prediction theory; least squares approximations; LMS; adaptive filters; closed-form expressions; correlation multiplier inputs; dynamic range; hardware implementation; least mean square; loop components; mean weight convergence; nonlinear variants; zero-memory limiters; Adaptive arrays; Adaptive filters; Convergence; Correlators; Dynamic range; Hardware; Interference; Least squares approximation; Phased arrays; Robustness;
Conference_Titel :
Military Communications Conference, 1989. MILCOM '89. Conference Record. Bridging the Gap. Interoperability, Survivability, Security., 1989 IEEE
Conference_Location :
Boston, MA
DOI :
10.1109/MILCOM.1989.103938
