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Orthogonal Polynomials in Two Variables by P. K. Suetin - 9789056991678
Orthogonal Polynomials in Two Variables by P. K. Suetin - 9789056991678
Orthogonal Polynomials in Two Variables by P. K. Suetin - 9789056991678
Orthogonal Polynomials in Two Variables by P. K. Suetin - 9789056991678

Orthogonal Polynomials in Two Variables by P. K. Suetin - 9789056991678

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Explore the complex mathematical world of Orthogonal Polynomials in Two Variables, a comprehensive text written by P. K. Suetin. This academic work serves as an essential resource for students, researchers, and mathematicians interested in approximation theory and functional analysis. The book provides a detailed look at the theory and application of polynomial expansions in higher dimensions, offering rigorous proofs and theoretical foundations. It is structured to guide readers through the properties, definitions, and specific examples of orthogonal polynomials, making it a valuable addition to any academic or reference library. Product Summary: This hardback book by P. K. Suetin focuses on the mathematical study of Orthogonal Polynomials in Two Variables, providing deep insights into multidimensional approximation techniques and advanced analysis.

Orthogonal Polynomials in Two Variables by P. K. Suetin - 9789056991678

Explore the complex mathematical world of Orthogonal Polynomials in Two Variables, a comprehensive text written by P. K. Suetin. This academic work serves as an essential resource for students, researchers, and mathematicians interested in approximation theory and functional analysis. The book provides a detailed look at the theory and application of polynomial expansions in higher dimensions, offering rigorous proofs and theoretical foundations. It is structured to guide readers through the properties, definitions, and specific examples of orthogonal polynomials, making it a valuable addition to any academic or reference library. Product Summary: This hardback book by P. K. Suetin focuses on the mathematical study of Orthogonal Polynomials in Two Variables, providing deep insights into multidimensional approximation techniques and advanced analysis.

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