Compression, Inversion, and Approximate PCA of Dense Kernel Matrices at Near-Linear Computational Complexity

Iterative learning control (ILC) is a technique to realize system inversion in a run-to-run manner. Though most of the techniques presented in the literature consider zero tracking error between the desired and achieved outputs, perfect inversion is often not feasible and in many cases not even desirable. Approximate inversion with good convergence and robustness properties (at the cost of a no...

In this paper we present different Monte Carlo algorithms to obtain inverse matrix. Here, we first determine two algorithms and describe their restrictions to be applicable for computing the inversion of a nonsingular matrix. Then, we establish an efficient algorithm to obtain approximate inversion of an arbitrary nonsingular matrix. This algorithm obtain an accurate inversion when the other tw...

An iterative predictor-corrector technique for the elimination of the approximate factorization errors which result from the factorization of linearized 0-methods in multidimensional reaction~iiffusion equations is proposed, and its convergence and linear stability are analyzed. Four approximate factorization techniques which do not account for the approximate factorization errors are developed...

Underground displacement monitoring is an effective method to explore deep into rock and soil masses for execution of subsurface displacement measurements. It is not only an important means of geological hazards prediction and forecasting, but also a forefront, hot and sophisticated subject in current geological disaster monitoring. In previous research, the authors had designed a novel electro...