The tensor spectral threshold decision problem is ∃R-hard via an explicit polynomial-time reduction from bounded quartic equality feasibility.
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A square root form of the second-order covariance update is presented for the first time, improving numerical accuracy and efficiency in recursive estimation algorithms.
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Tensor Spectral Threshold is $\exists\mathbb{R}$-Hard
The tensor spectral threshold decision problem is ∃R-hard via an explicit polynomial-time reduction from bounded quartic equality feasibility.
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Covariance Square Root Second-Order Mapping
A square root form of the second-order covariance update is presented for the first time, improving numerical accuracy and efficiency in recursive estimation algorithms.