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- W2067058051 abstract "This paper is motivated by sensing and wireless communication, where data compression or dimension reduction may be used to reduce the required communication bandwidth. High-dimensional measurements are converted into low-dimensional representations through linear compression. Our aim is to compress a noisy sensor measurement, allowing for the fact that the compressed measurement will then be transmitted over a noisy channel. We give the closed-form expression for the optimal compression matrix that minimizes the trace or determinant of the error covariance matrix. We show that the solutions share a common architecture consisting of a canonical coordinate transformation, scaling by coefficients which account for canonical correlations and channel noise variance, followed by a coordinate transformation into the sub-dominant invariant subspace of the channel noise." @default.
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- W2067058051 date "2013-11-01" @default.
- W2067058051 modified "2023-09-23" @default.
- W2067058051 title "Scaled canonical coordinates for compression and transmission of noisy sensor measurements" @default.
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- W2067058051 doi "https://doi.org/10.1109/acssc.2013.6810308" @default.
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