Maths for Chemists Vol 2: Power Series, Complex Numbers and Linear Algebra (Tutorial Chemistry Texts)

Martin C.R. Cockett, Graham Doggett, "Maths for Chemists Vol 2: Power Series, Complex Numbers and Linear Algebra (Tutorial Chemistry Texts)"
Royal Society of Chemistry | 2003-10-21 | ISBN: 0854044957 | 200 pages | PDF | 29,5 MB

The two volumes of "Maths for Chemists" provide a resource for all undergraduate chemistry students, but are particularly focused on the needs of students who may not have studied mathematics beyond GCSE level (or equivalent). The texts are introductory in nature and adopt a sympathetic approach for students who need support and understanding in working with the diverse mathematical tools required in a typical chemistry degree course. Volume II builds on the foundations laid in Volume I, and goes on to develop more advanced material. The topics covered include: power series, which are used to formulate alternative representations of functions and are important in model building in chemistry; complex numbers and complex functions, which appear in quantum chemistry, spectroscopy and crystallography; matrices and determinants used in the solution of sets of simultaneous linear equations and in the representation of geometrical transformations used to describe molecular symmetry characteristics; and vectors which allow the description of directional properties of molecules.

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Linear Matrix Inequalities in System and Control Theory

Linear Matrix Inequalities in System and Control Theory (Studies in Applied and Numerical Mathematics)

Linear Matrix Inequalities in System and Control Theory (Studies in Applied and Numerical Mathematics): Venkataramanan Balakrishnan, Eric Feron, Laurent El Ghaoui
Society for Industrial Mathematics | ISBN: 0898714850 | 1997-06-26 | djvu (ocr) | 193 pages | 1.58 Mb
In this book the authors reduce a wide variety of problems arising in system and control theory to a handful of convex and quasiconvex optimization problems that involve linear matrix inequalities. These optimization problems can be solved using recently developed numerical algorithms that not only are polynomial-time but also work very well in practice; the reduction therefore can be considered a solution to the original problems. This book opens up an important new research area in which convex optimization is combined with system and control theory, resulting in the solution of a large number of previously unsolved problems.

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