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In this paper, we propose prominent subspace least-mean-square (PS-LMS) algorithms for fast identification of time-varying system. It is shown that the dimensionality of system identification can be dramatically reduced if the unknown system is sparse in the sense that its parameter set has a skewed statistical distribution when expressed in a proper basis. In such cases, the system identification...
In many system identification applications, the unknown system is characterized by time-varying parameters. Therefore, fast on-line identification is required in order to keep the system stable and improve the control performance. In this paper, we show that the dimensionality of system identification can be dramatically reduced if the unknown system is sparse, in the sense that its parameter set...
Online secondary path modeling is used to deal with varying secondary path in active control systems. However, instability may happen when there is fast "significant" changing due to the tracking speed limitation of online secondary path modeling. In this paper a scheme involving analogue compensator is proposed to be used in the secondary path with fast "significant" changing...
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