The normal linear model, with sign or other linear inequality constraints on its coefficients, arises very commonly in many scientific applications. Given inequality constraints Bayesian inference is ...
Abstract In this paper, we first study the solution to linear matrix inequality AXB + (AXB)* ⩾ (>, ⩽, <) C when the matrix G = (A B*) is full row rank, where C is a Hermitian matrix. Furthermore, for ...
The inequality will be solved when \({m}\) is isolated on one side of the inequality. This can be done by using inverse operations on each stage of the sum. The final answer is ...
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