A decomposition method for positive semidefinite matrices and its application to recursive parameter estimation (Q2706309)
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scientific article
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | A decomposition method for positive semidefinite matrices and its application to recursive parameter estimation |
scientific article |
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19 March 2001
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positive semidefinite matrices
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matrix decomposition
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rank additivity
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least squares method
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recursive estimation
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parameter estimation algorithm
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0.8843926
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0.87973493
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0.8746111
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0.8729648
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0.87275726
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0.87040925
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A decomposition method for positive semidefinite matrices and its application to recursive parameter estimation (English)
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The authors deal with the problem to decompose a positive semidefinite matrix \(A\) into a sum of two positive semidefinite matrices \(B\) and \(C,\) \(A=B+C,\) subject to certain rank and orthogonality conditions. They call this an orthogonal decomposition along a subspace. They show that it has the rank additivity property, \(\text{rank} A=\text{rank} B+\text{rank} C.\) This decomposition is then used to develop a new recursive parameter estimation algorithm for linear systems.
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