DocumentCode :
1408259
Title :
Linear Systems, Sparse Solutions, and Sudoku
Author :
Babu, Prabhu ; Pelckmans, Kristiaan ; Stoica, Petre ; Li, Jian
Author_Institution :
Dept. of Inf. Technol., Uppsala Univ., Uppsala, Sweden
Volume :
17
Issue :
1
fYear :
2010
Firstpage :
40
Lastpage :
42
Abstract :
In this paper, we show that Sudoku puzzles can be formulated and solved as a sparse linear system of equations. We begin by showing that the Sudoku ruleset can be expressed as an underdetermined linear system: Ax = b, where A is of size m times n and n > m. We then prove that the Sudoku solution is the sparsest solution of Ax = b, which can be obtained by lo norm minimization, i.e. min ||x:||0 s.t. Ax = b. Instead of this minimization SB problem, inspired by the sparse representation literature, we solve the much simpler linear programming problem of minimizing the l1 norm of x, i.e. min ||x||1 s.t. Ax = b, and show numerically that this approach solves representative Sudoku puzzles.
Keywords :
linear programming; minimisation; Sudoku puzzles; linear programming; norm minimization; sparse linear system; sparse solutions; $l_{0}$ norm minimization; $l_{1}$ norm minimization; Linear systems; Sudoku; sparse representation;
fLanguage :
English
Journal_Title :
Signal Processing Letters, IEEE
Publisher :
ieee
ISSN :
1070-9908
Type :
jour
DOI :
10.1109/LSP.2009.2032489
Filename :
5247059
Link To Document :
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