Linear Algebra and Its ApplicationsJohn Wiley & Sons, 2007/09/10 - 392 ページ This set features Linear Algebra and Its Applications, Second Edition (978-0-471-75156-4) Linear Algebra and Its Applications, Second Edition presents linear algebra as the theory and practice of linear spaces and linear maps with a unique focus on the analytical aspects as well as the numerous applications of the subject. In addition to thorough coverage of linear equations, matrices, vector spaces, game theory, and numerical analysis, the Second Edition features student-friendly additions that enhance the book's accessibility, including expanded topical coverage in the early chapters, additional exercises, and solutions to selected problems. Beginning chapters are devoted to the abstract structure of finite dimensional vector spaces, and subsequent chapters address convexity and the duality theorem as well as describe the basics of normed linear spaces and linear maps between normed spaces. Further updates and revisions have been included to reflect the most up-to-date coverage of the topic, including:
Clear, concise, and superbly organized, Linear Algebra and Its Applications, Second Edition serves as an excellent text for advanced undergraduate- and graduate-level courses in linear algebra. Its comprehensive treatment of the subject also makes it an ideal reference or self-study for industry professionals. and Functional Analysis (978-0-471-55604-6) both by Peter D. Lax. |
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2007 John Wiley a₁ According to Theorem adjoint algorithm Applications belongs called Chapter characteristic polynomial coefficients commute complex numbers components converges convex set Copyright 2007 John Corollary deduce defined definition denote determinant diagonal entries differentiable dimension dimensional eigenvalues eigenvectors equal equation Euclidean space Euclidean structure EXERCISE finite finite-dimensional follows formula h₁ inequality integral invertible isometry isomorphism Lax Copyright 2007 Lemma Linear Algebra linear combination linear function linear map linearly independent Lorentz transformation matrix multiplication nonnegative nonzero normed linear space nullspace orthogonal polynomial of degree positive proof of Theorem properties real numbers rewrite right-hand side root rotation satisfies scalar product self-adjoint mapping self-adjoint matrices sequence Show solution spectral spectral theory subspace Suppose symmetric symplectic matrix tends to zero Theorem 11 transpose Wiley & Sons x₁