Abstract: Designing the transmit waveforms with prescribed ambiguity functions (AFs) and beampatterns while adhering to the constant modulus (CM) constraint is pivotal for the forthcoming cognitive ...
ABSTRACT: The Laplacian of a function measures the difference between the value of the function at a point and its average around that point. It is a differential operator appears in many differential ...
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Abstract: EEG signal classification using Riemannian manifolds has shown great potential. However, the huge computational cost associated with Riemannian metrics poses challenges for applying ...
LAI, ZHIJIAN and YOSHISE, AKIKO,2021. The code is based on matalb solver 'Manopt'. problem.M % manifold problem.actualcost = @(x) % actual cost function, or other functions used to evaluate the ...
ABSTRACT: We establish the links between the lightlike geometry and basics invariants of the associated semi-Riemannian geometry on r-lightlike submanifold and semi-Riemannian constructed from a ...
Manifold fitting, a crucial challenge in nonlinear data analysis, holds immense potential for efficient and accurate modeling. However, existing methods struggle to balance accuracy and computational ...
And then there is dude cooking. Dude cooking has very little to do with actual food, though sometimes a good meal can come out of it. But that’s just a pleasant side effect. Dude cooking is all about ...
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