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A rectangular Vandermonde matrix \(V=\{V_{ij}\}= \{x_i^{j-1}\}\) \((i=1,\dots, n;\;j=1,\dots, m;\;n\leq m)\) defined on the so-called Chebyshev nodes (the roots of Chebyshev polynomials of the first order) is studied, by making use of combinatorial identities from number theory [cf. \textit{A. Eisinberg}, \textit{P. Pugliese}, and \textit{N. Salerno}, Numer. Math. 87, No. 4, 663--674 (2001; Zbl 0974.65029); \textit{A. Eisinberg}, \textit{G. Franzé}, and \textit{P. Puyliese}, Linear Algebra Appl. 283, No. 1-3, 205--219 (1998; Zbl 0935.65016) and Numer. Math. 80, No. 1, 75--85 (1998; Zbl 0913.65022)]. The explicit factorizations \(V=HUD\) as well as \(V^+= (1/n)D^{-1}QBH^T\) are presented, where \(H\) is rectangular, \(U\) and \(Q=U^{-1}\) are triangular, \(D\) and \(B\) \((B_{1,1}= 1;\;B_{i,i}=2;\;i=2,\dots,n)\) are diagonal matrices. It is proved that the so-called condition number [cf. \textit{G. H. Golub} and \textit{C. F. Van Loan}, Matrix computations, 2nd ed. (1989; Zbl 0733.65016), 1. Aufl. (Zbl 0559.65011)] of the matrix \(V\) does not depend on the dimension of the nodes sets. Numerical experiments are also performed and, as a result, some numerical properties of the proposed formulae are established.
Numerical Analysis, Algebra and Number Theory, Combinatorial identities, Numerical computation of matrix norms, conditioning, scaling, Vandermonde matrices, Combinatorics in computer science, Least square method, Factorization of matrices, factorizations, Conditioning of matrices, combinatorial identities, rectangular Vandermonde matrix, Least squares and related methods for stochastic control systems, roots of Chebyshev polynomials, Discrete Mathematics and Combinatorics, Hermitian, skew-Hermitian, and related matrices, Theory of matrix inversion and generalized inverses, Geometry and Topology, Chebyshev polynomials, numerical experiments, condition number
Numerical Analysis, Algebra and Number Theory, Combinatorial identities, Numerical computation of matrix norms, conditioning, scaling, Vandermonde matrices, Combinatorics in computer science, Least square method, Factorization of matrices, factorizations, Conditioning of matrices, combinatorial identities, rectangular Vandermonde matrix, Least squares and related methods for stochastic control systems, roots of Chebyshev polynomials, Discrete Mathematics and Combinatorics, Hermitian, skew-Hermitian, and related matrices, Theory of matrix inversion and generalized inverses, Geometry and Topology, Chebyshev polynomials, numerical experiments, condition number
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