1990
DOI: 10.1016/s1474-6670(17)51997-7
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Selective Forgetting in Adaptive Procedures

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Cited by 16 publications
(6 citation statements)
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“…In [44][45][46] non-uniformly distributed information is dealt with by selective amplification of the covariance matrix, called directional forgetting. Similarly, [47,48] propose vector-type or selective forgetting, were individual parameter dependent forgetting factors are used, to deal with the effects of time-scale separation. The design of an advanced online parameter identification algorithm for the PH-LAB is out of the scope of this research.…”
Section: Hyperparametersmentioning
confidence: 99%
“…In [44][45][46] non-uniformly distributed information is dealt with by selective amplification of the covariance matrix, called directional forgetting. Similarly, [47,48] propose vector-type or selective forgetting, were individual parameter dependent forgetting factors are used, to deal with the effects of time-scale separation. The design of an advanced online parameter identification algorithm for the PH-LAB is out of the scope of this research.…”
Section: Hyperparametersmentioning
confidence: 99%
“…Secondly, to cope with the different dynamics of parameters variation, a vector-type forgetting factor should be employed [31,32]. This method is known as an efficient approach to simultaneously keep different-dynamic-rate parameters on track [33,34].…”
Section: Multiple Adaptive Forgetting Factors Rls Estimationmentioning
confidence: 99%
“…In the case that the parameters in ARX model ( 1) vary with a different rate it is desirable to assign different forgetting factors. The RLS with vector-type forgetting scheme, [18], [15], consists of scaling P t by a diagonal matrix Λ of forgetting factors…”
Section: State Of the Artmentioning
confidence: 99%
“…An ad-hoc remedy to estimate parameters with different changing rates is the RLS with vector-type forgetting (or selective forgetting) scheme, [19], [18], [15], [16]. The idea of the above method is to introduce many forgetting factors reflecting the different rates of the change of the parameters.…”
Section: Introductionmentioning
confidence: 99%