The theory of "continuous learning" is applied here to the design of nonlinear sampled-data trackers. This theory provides a continuous-motion approximation of the discrete or sampled motion of the actual tracker. The theory prodicts the transient-response performance of the tracker as well as the mean-square errors caused by noise and statistical fluctuations in the signal. Numerical examples of first-order and second-order trackers designed by this technique are presented. These examples illustrate the adaptive behavior predicted by the technique. In one of these examples the trade-off between transient-response performance and the suppression of noise-induced tracking errors is demonstrated.
Adaptive Trackers Based on Continuous Learning Theory
IEEE Transactions on Aerospace and Electronic Systems ; AES-10 , 2 ; 245-254
1974-03-01
2471512 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Learning-based dynamic coupling of discrete and continuous trackers
British Library Online Contents | 2006
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SPIE | 1989
|Online Contents | 1995
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