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A key problem in optimal input design is that the optimal input depends on some unknown system parameters that are to be identified. Adaptive design is one of the fundamental routes to handle this problem. This paper proposes an adaptive input design method for ARMAX systems based on the general stochastic framework outlined in the reference [10].
Based on recent advances on convex design for Large-Scale Control Systems (LSCSs) and robust and efficient LSCS self-tuning/adaptation, a methodology is proposed in this paper which aims at providing an integrated LSCS-design, applicable to large-scale systems of arbitrary scale, heterogeneity and complexity and capable of: 1) Providing stable, efficient and arbitrarily-close-to-optimal LSCS performance;...
In this paper a new approach to formulate the constrained Linear Quadratic Regulator (LQR) problem as a Quadratic Programming (QP) problem is introduced. The new approach takes advantage of the (Moore-Penrose) generalized inverse to eliminate control inputs as decision variables, hence the optimization is performed only over the states belonging to the prediction horizon. This allows one to save on...
Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES) is arguably one of the most powerful stochastic real-parameter optimization algorithms in current use for non-linear non-convex functions with parameter linkages. Differential Evolution (DE) is again a very powerful but simple evolutionary algorithm for real parameter optimization. In this article we propose a simple but very efficient hybrid...
A comprehensive, analytical framework for MR-DTI is constructed in a linear algebra setup. The expressions describing the effects of imaging gradients show formulation ambiguities. Center-symmetric gradient schemes use no cross terms (NoCroT) in the calculations resulting, at least in theory, in the alleviation of the issue. When three estimation methods, all gradients, NoCroT and diffusion gradients...
Graph Bisection is the problem of partitioning the vertices of a graph into two equal-size pieces so as to minimize the number of edges between the two pieces. This paper presents an algorithm that will, for almost all graphs in a certain class, output the minimum-size bisection. Furthermore the algorithm will yield, for almost all such graphs, a proof that the bisection is optimal. The algorithm...
We present parallel algorithms to compute the determinant and characteristic polynomial of n×n-matrices and the gcd of polynomials of degree ≤n. The algorithms use parallel time O(log2n) and a polynomial number of processors. We also give a fast parallel Las Vegas algorithm for the rank of matrices. All algorithms work over arbitrary fields.
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