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A global optimization method for continuous-time adaptive recursive filters

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4 Author(s)
Edmonson, W. ; Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL, USA ; Palacios, J.C. ; Chang An Lai ; Latchman, H.

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.

Published in:

Signal Processing Letters, IEEE  (Volume:6 ,  Issue: 8 )