Abstract

Optimal recursive system parameter estimation has been applied to a phase locked loop (PLL) since the 1950s. Application to a PLL results in a second order, type II PLL. This type of PLL is NOT robust to parametric variations in the components of a PLL. The cause of this lack of robustness illustrates the main problem with optimal recursive linear system parameter estimation. Solution of this problem can then be extended from commercial PLLs to the general problems encountered in adaptive control, neural networks, neuro-biological information transfer, and the Heisenberg uncertainty principle.

Bio

Since 2000, Don has been teaching and researching at UCSC in both Department of Electrical and Department of Computer Engineering at UCSC, and was a researcher in the Center for Adaptive Optics there (2001 - 2011). Don is a Life Fellow of IEEE. Don retired as Professor of Engineering and Applied Science in the Electrical Engineering Department at UCLA in 1994, after 29 years there. He was also Professor of Anesthesiology at UCLA. In 1995 he served as Senator Tom Harkin’s (Dem. IA) Legislative Assistant in Defense Appropriations, Energy, Environment, Arms Control, and Veteran’s Affairs as IEEE Congressional Fellow. He was a Fulbright Senior Fellow in Denmark in 1976-7 and in Norway in 1983-4, and he visited at DFVLR, Munich, 1969-70, University of Newcastle, Australia, 1989-90, University of Maryland, 1993-94, and Ajou University, Suwan, South Korea, 2006-07.