Linear Algebra, Geometry and Transformation

The Essentials of a First Linear Algebra Course and More Linear Algebra, Geometry and Transformation provides students with a solid geometric grasp of linear transformations. It stresses the linear case of the inverse function and rank theorems and gives a careful geometric treatment of the spectral theorem. An Engaging Treatment of the Interplay among Algebra, Geometry, and Mappings The text starts with basic questions about images and pre-images of mappings, injectivity, surjectivity, and distortion. In the process of answering these questions in the linear setting, the book covers all the standard topics for a first course on linear algebra, including linear systems, vector geometry, matrix algebra, subspaces, independence, dimension, orthogonality, eigenvectors, and diagonalization. A Smooth Transition to the Conceptual Realm of Higher Mathematics This book guides students on a journey from computational mathematics to conceptual reasoning. It takes them from simple "identity verification" proofs to constructive and contrapositive arguments. It will prepare them for future studies in algebra, multivariable calculus, and the fields that use them. Print Versions of this book also include access to the ebook version.

Vectors, Mappings and Linearity Numeric Vectors Functions Mappings and Transformations Linearity The Matrix of a Linear Transformation Solving Linear Systems The Linear SystemThe Augmented Matrix and RRE Form Homogeneous Systems in RRE Form Inhomogeneous Systems in RRE Form The Gauss-Jordan Algorithm Two Mapping Answers Linear Geometry Geometric Vectors Geometric/Numeric Duality Dot-Product Geometry Lines, Planes, and Hyperplanes System Geometry and Row/Column Duality The Algebra of Matrices Matrix Operations Special Matrices Matrix Inversion A Logical Digression The Logic of the Inversion Algorithm Determinants Subspaces Basic Examples and Definitions Spans and Perps Nullspace Column-Space Perp/Span Conversion Independence Basis Dimension and Rank Orthogonality Orthocomplements Four Subspaces, 16 Questions Orthonormal Bases The Gram-Schmidt Algorithm Linear Transformation Kernel and Image The Linear Rank Theorem Eigenspaces Eigenvalues and Eigenspaces: Calculation Eigenvalues and Eigenspaces: Similarity Diagonalizability and the Spectral Theorem Singular Value Decomposition Appendix A: Determinants Appendix B: Proof of the Spectral TheoremAppendix C: Lexicon Index

Bruce Solomon is a professor in the Department of Mathematics at Indiana University Bloomington, where he often teaches linear algebra. He has held visiting positions at Stanford University and in Australia, France, and Israel. His research articles explore differential geometry and geometric variational problems. He earned a PhD from Princeton University.