A new matrix decomposition for signal processing
نویسندگان
چکیده
SUBTITLE. Despite its important signal processing applications, the generalized singular value decomposition (GSVD) is under-utilized due to the high updating cost. In this paper, we introduce a new approximate GSVD that is easily amenable to updating. ABSTRACT. To solve the noise subspace problem, we extend the generalized singular value decomposition to a new decomposition that can be updated at a low cost. In addition, we show how a forgetting factor can be incorporated in our new decomposition.
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عنوان ژورنال:
- Automatica
دوره 30 شماره
صفحات -
تاریخ انتشار 1994