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The derivation and implementation of many algorithms in sig-nal/image processing and control involve some form of polynomial root-finding and/or matrix eigendecomposition. In this paper, higher order fixed point functions in rational and/or radical forms are developed. This set of iterations can be considered as extensions of known methods such as Newton's,… (More)

In thas paper, we have developed an appronch for fzp-proximating the signal and noise suhspnws which avoid the costly eigendecomposataon or SVD. Th~sc subspac~s were approximated using ratzonal and power-lake methods applied to the sample covariance matrix. It 2s shown that MUSIC nnrl Minirnulrr Norm frequency es-timators can he derived using these… (More)

Fast algorithms based on the matrix sign function are developed to estimate the signal and noise subspaces of the sample correlation matrices. These subspaces are then utilized to develop high resolution methods such as MUSIC and ESPRIT for sinusoidal frequency and direction of arrival DOA problems. The main feature of these algorithms is that they generate… (More)

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