Model Selection with Componentwise Shrinkage in Orthogonal Regression(Digital Signal Processing)

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概要

• 論文の詳細を見る

• In the problem of determining the major frequency components of a signal disturbed by noise, a model selection criterion has been proposed. In this paper, the criterion has been extended to cover a penalized cost function that yields a componentwise shrinkage estimator, and it exhibited a consistent model selection when the proposed criterion was used. Then, a simple numerical simulation was conducted, and it was found that the proposed criterion with an empirically estimated componentwise shrinkage estimator outperforms the original criterion.

• 社団法人電子情報通信学会の論文
• 2003-07-01

著者

• Hagiwara K

  Department Of Intelligence & Computer Science Nagoya Institute Of Technology

• HAGIWARA Katsuyuki

  Department of Intelligence & Computer Science, Nagoya Institute of Technology

関連論文

• Model Selection with Componentwise Shrinkage in Orthogonal Regression(Digital Signal Processing)

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