M-M.E.S.S. provides low-rank solvers for large-scale symmetric matrix equations with sparse or sparse + low-rank coefficients. The main focus is on differential and algebraic Riccati equations ...
Analysis and Application of Matrix-Form Neural Networks for Fast Matrix-Variable Convex Optimization
Abstract: Matrix-variable optimization is a generalization of vector-variable optimization and has been found to have many important applications. To reduce computation time and storage requirement, ...
ParaMonte has been developed while bearing the following design goals in mind: Full automation of Monte Carlo and Machine Learning simulations as much as possible to ensure user-friendliness of the ...
Abstract: In this paper, a sliding mode – model predictive controller for a BLDC motor has been designed and implemented. This cascade controller consists of two loops, the inner loop is a sliding ...
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