Title :
A global optimization method for continuous-time adaptive recursive filters
Author :
Edmonson, William ; Palacios, Juan Carlos ; Lai, Chang An ; Latchman, Haniph
Author_Institution :
Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL, USA
Abstract :
A major drawback of recursive adaptive filters based on gradient methods is that convergence to a global minimum is not always achieved. This is due to a nonconvex mean square error (MSE) performance surface. This article develops a continuous-time least mean square algorithm that converges to the global minimum with probability one.
Keywords :
IIR filters; adaptive filters; circuit optimisation; continuous time filters; convergence of numerical methods; filtering theory; least mean squares methods; probability; recursive filters; IIR filter; MSE performance surface; continuous-time adaptive recursive filters; continuous-time least mean square algorithm; convergence; global optimization method; gradient methods; nonconvex mean square error; probability; Adaptive filters; Convergence; Gradient methods; Least mean square algorithms; Least squares approximation; Mean square error methods; Optimization methods; Signal processing algorithms; Stochastic processes; Taylor series;
Journal_Title :
Signal Processing Letters, IEEE
