Feedback Stabilization over Commutative Rings: The Matrix Case

1994 ◽  
Vol 32 (6) ◽  
pp. 1675-1695 ◽  
Author(s):  
V. R. Sule
1953 ◽  
Vol 49 (4) ◽  
pp. 595-600 ◽  
Author(s):  
M. P. Drazin

It is well known that the elements of any given commutative algebra (and hence of any commutative set) of n × n matrices, over an algebraically closed field K, have a common eigenvector over K; indeed, the elements of such an algebra can be simultaneously reduced to triangular form (by a suitable similarity transformation). McCoy (5) has shown that a triangular reduction is always possible even for matrix algebras satisfying a condition substantially weaker than commutativity. Our aim in this note is to extend these results to more general systems (our arguments being, incidentally, simpler than some used for the matrix case even by writers subsequent to McCoy).


2012 ◽  
Vol 62 (6) ◽  
pp. 1451-1466 ◽  
Author(s):  
Teodor Banica ◽  
Adam Skalski ◽  
Piotr Sołtan

ISRN Algebra ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
N. S. Dzhaliuk ◽  
V. M. Petrychkovych

The method of solving matrix linear equations and over commutative Bezout domains by means of standard form of a pair of matrices with respect to generalized equivalence is proposed. The formulas of general solutions of such equations are deduced. The criterions of uniqueness of particular solutions of such matrix equations are established.


2020 ◽  
Vol 35 (4) ◽  
pp. 247-261
Author(s):  
Dmitry Zheltkov ◽  
Eugene Tyrtyshnikov

AbstractIn contrast to many other heuristic and stochastic methods, the global optimization based on TT-decomposition uses the structure of the optimized functional and hence allows one to obtain the global optimum in some problem faster and more reliable. The method is based on the TT-cross method of interpolation of tensors. In this case, the global optimum can be found in practice even in the case when the approximation of the tensor does not possess a high accuracy. We present a detailed description of the method and its justification for the matrix case and rank-1 approximation.


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