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• W2412867837 abstract "Among many methods for Automatic Target Recognition (ATR), Quadratic Correlation Filters (QCF) have become popular. Recently, the Rayleigh Quotient Quadratic Correlation filters (RQQCF) technique was proposed to optimize QCF's for ATR by explicitly maximizing a class separation metric. The method requires the Eigenvalue Decomposition (EVD) of a large matrix, which is obtained using the autocorrelation matrices of target and clutter training images. Often, in practice, when few new targets and clutter need to be incorporated, the EVD is perturbed. It is desirable to have methods that eliminate the need to perform an EVD every time new data is to be added. In this paper, a novel method is proposed to obtain the new EVD adaptively, starting from the initial EVD, leading to significant computational savings. Sample results using synthetic datasets confirm the excellent properties of the technique." @default.
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• W2412867837 date "2006-07-13" @default.
• W2412867837 modified "2023-09-24" @default.
• W2412867837 title "A novel adaptive eigendecomposition technique with application to automatic target recognition" @default.
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