scholarly journals Linear Discrepancy of Basic Totally Unimodular Matrices

10.37236/1526 ◽  
2000 ◽  
Vol 7 (1) ◽  
Author(s):  
Benjamin Doerr

We show that the linear discrepancy of a basic totally unimodular matrix $A \in R^{m \times n}$ is at most $1- {1\over {n+1}}$. This extends a result of Peng and Yan.


COMBINATORICA ◽  
2004 ◽  
Vol 24 (1) ◽  
pp. 117-125 ◽  
Author(s):  
Benjamin Doerr


2007 ◽  
Vol 420 (2-3) ◽  
pp. 663-666 ◽  
Author(s):  
Benjamin Doerr


Author(s):  
Samsul Arifin ◽  
Indra Bayu Muktyas

An SPL can be represented as a multiplication of the coefficient matrix and solution vector of the SPL. Determining the solution of an SPL can use the inverse matrix method and Cramer's rule, where both can use the concept of the determinant of a matrix. If the coefficient matrix is a unimodular matrix, then all solutions of an SPL are integers. In this paper we will present a method of generating a unimodular matrix using Python so that it can be utilized on an SPL. Keywords: SPL, Unimodular Matrix, Python



1957 ◽  
Vol 9 ◽  
pp. 47-59
Author(s):  
A. T. Butson

1. Introduction. Let be a Boolean ring of at least two elements containing a unit 1. Form the set of matrices A, B, … of order n having entries aiJ, bij, … (i, j = 1, 2, …, n), which are members of . A matrix U of is called unimodular if there exists a matrix V of such that VU= I, the identity matrix. Two matrices A and B are said to be left-associates if there exists a unimodular matrix U satisfying UA = B.



Order ◽  
2007 ◽  
Vol 24 (3) ◽  
pp. 139-153 ◽  
Author(s):  
David M. Howard ◽  
Mitchel T. Keller ◽  
Stephen J. Young




2003 ◽  
Vol 10 ◽  
Author(s):  
Geir Dahl
Keyword(s):  




Order ◽  
2005 ◽  
Vol 22 (1) ◽  
pp. 63-72 ◽  
Author(s):  
Sungpyo Hong ◽  
Jong-Yoon Hyun ◽  
Hyun Kwang Kim ◽  
Sang-Mok Kim
Keyword(s):  


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