by Karl Petersen
Publisher: University of North Carolina 2008
Number of pages: 65
These notes provide an introduction to the subject of measure-preserving dynamical systems, discussing the dynamical viewpoint; how and from where measure-preserving systems arise; the construction of measures and invariant measures; some basic constructions within the class of measure-preserving systems; and some mathematical background on conditional expectations, Lebesgue spaces, and disintegrations of measures.
Download or read it online for free here:
by Sanjeev Arora, Boaz Barak - Cambridge University Press
The book provides an introduction to basic complexity classes, lower bounds on resources required to solve tasks on concrete models such as decision trees or circuits, derandomization and pseudorandomness, proof complexity, quantum computing, etc.
by Allen B. Downey - Green Tea Press
This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science. The book focuses on discrete models, which include graphs, cellular automata, and agent-based models.
by Neil D. Jones - The MIT Press
The author builds a bridge between computability and complexity theory and other areas of computer science. Jones uses concepts familiar from programming languages to make computability and complexity more accessible to computer scientists.
by Oded Goldreich - Cambridge University Press
This book offers a comprehensive perspective to modern topics in complexity theory. It can be used as an introduction as either a textbook or for self-study, or to experts, since it provides expositions of the various sub-areas of complexity theory.