Yi Ma

Shankar Sastry

René Vidal

This book provides a comprehensive introduction to the latest advances in the mathematical theory and computational tools for modeling high-dimensional data drawn from one or multiple low-dimensional subspaces (or manifolds) and potentially corrupted by noise, gross errors, or outliers. This challenging task requires the development of new algebraic, geometric, statistical, and computational methods for efficient and robust estimation and segmentation of one or multiple subspaces. The book also presents interesting real-world applications of these new methods in image processing, image and video segmentation, face recognition and clustering, and hybrid system identification etc. This book is intended to serve as a textbook for graduate students and beginning researchers in data science, machine learning, computer vision, image and signal processing, and systems theory. It contains ample illustrations, examples, and exercises and is made largely self-contained with three Appendices which survey basic concepts and principles from statistics, optimization, and algebraic-geometry used in this book. René Vidal is a Professor of Biomedical Engineering and Director of the Vision Dynamics and Learning Lab at The Johns Hopkins University. Yi Ma is Executive Dean and Professor at the School of Information Science and Technology at ShanghaiTech University. S. Shankar Sastry is Dean of the College of Engineering, Professor of Electrical Engineering and Computer Science and Professor of Bioengineering at the University of California, Berkeley.

Generalized Principal Component Analysis

Anil Nerode

Wolf Kohn

Panos Antsaklis

This book documents the scientific outcome of the Third International Workshop on Hybrid Systems, held in Ithaca, NY, USA, in October 1994. It presents a selection of carefully reviewed and revised full papers chosen from the workshop contribution and is the successor to LNCS 736, the seminal "Hybrid Systems" volume edited by Grossman, Nerode, Ravn, and Rischel. Hybrid systems are models for networks of digital and continuous devices, in which digital control programs sense and supervise continuous and discrete plants governed by differential or difference equations. The investigation of hybrid systems is creating a new and fascinating discipline bridging mathematics, computer science, and control engineering.

Hybrid Systems II

Panos J. Antsaklis

Michael Lemmon

This book constitutes the strictly refereed post-proceedings of the 5th International Hybrid Systems Workshop held in Notre Dame, Indiana, USA in September 1998. The 23 revised full papers presented in the book have gone through two rounds of thorough reviewing and revision. The volume presents state-of-the-art research results and particularly addresses such areas as program verification, concurrent and distributed processes, logic programming, logics of programs, discrete event simulation, calculus of variations, optimization, differential geometry, Lie algebras, automata theory, dynamical systems, etc.

Shankar Sastry

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