Iterative methods use successive approximations to obtain more accurate solutions. Iterative Methods and Preconditioners for Systems of Linear Equations
presents historical background, derives complete convergence estimates for all methods, illustrates and provides Matlab codes for all methods, and studies and tests all preconditioners first as stationary iterative solvers.
This textbook is appropriate for undergraduate and graduate students in need of an overview or of deeper knowledge about iterative methods. It can be used in courses on Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory. Scientists and engineers interested in new topics and applications will also find the text useful.
Martin J. Gander is a full professor in mathematics at the University of Geneva. He was previously a postdoctoral fellow at École Polytechnique in Paris, and professor of Mathematics at McGill University. He has held visiting positions at Paris 13, University of Nice, RICAM, University of Amiens, Xi'an Jiaotong University, Institut National Polytechnique de Toulouse, University Henri Poincaré, and the CNRS. Professor Gander held the Pólya Fellowship at Stanford, a TMR Fellowship from the Swiss National Science Foundation, and an FCAR strategic professorship from Quebec. Together with Felix Kwok, he won the SIAM 100-Dollar 100-Digit Challenge, and with Albert Ruehli the best paper award at the 19th IEEE EPEPS conference. He became a SIAM fellow in 2020 and was nominated the Jean-Morlet Chair of the CIRM for 2022. His main research interest is numerical analysis, specifically parallel iterative methods for space-time problems.
Gabriele Ciaramella is an assistant professor with tenure at the Politecnico di Milano (MOX Lab). He was a postdoctoral Fellow at University of Geneva and Junior Professor at the University of Konstanz. His main research interests are in numerical analysis, specifically parallel iterative methods, and in numerical optimization with applications to quantum systems.
