The main objective of this code is to provide different identification methods to build linear models of dynamic systems, starting from input-output collected data. The models can be built as transfer ...

In the last episode of my column in Notices of the American Mathematical Society, we looked at a particle moving in an attractive central force whose strength is proportional to the inverse cube of ...

projection_target_subspace projection_targetfree_subspace ax_targets, ax_targetfree target_subspace_signal targetfree_subspace_signal target_subspace_var targetfree_subspace_var total_var ...

Abstract: Localizing more sources than sensors with a sparse linear array (SLA) has long relied on minimizing a distance between two covariance matrices and recent algorithms often utilize ...

In the past few decades, multi-linear algebra also known as tensor algebra has been adapted and employed as a tool for various engineering applications. Recent developments in tensor algebra have ...

Abstract: In this paper, a general optimization formulation is proposed for the subspace segmentation by low rank representation via the sparse-prompting quasi-rank function. We prove that, with the ...

Department of Mathematics, Harbin University of Science and Technology, Harbin, China. 1. Related Properties of Generalized Orthogonal Group and Generalized Orthogonal Basis Orthogonality is an ...

Metric geometry is a considerable extension of Riemannian geometry that, in recent decades, has proven very useful. A newer direction described in this article can moreover be viewed as an extension ...

The phenomenon of benign overfitting is one of the key mysteries uncovered by deep learning methodology: deep neural networks seem to predict well, even with a perfect fit to noisy training data.