Despite growing interest, basic information on methods and models for mathematically analyzing algorithms has rarely been directly accessible to practitioners, researchers, or students. An Introduction to the Analysis of Algorithms, Second Edition, organizes and presents that knowledge, fully introducing primary techniques and results in the field. Robert Sedgewick and the late Philippe Flajolet have drawn from both classical mathematics and computer science, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures. They emphasize the mathematics needed to support scientific studies that can serve as the basis for predicting algorithm performance and for comparing different algorithms on the basis of performance. Techniques covered in the first half of the book include recurrences, generating functions, asymptotics, and analytic combinatorics. Structures studied in the second half of the book include permutations, trees, strings, tries, and mappings. Numerous examples are included throughout to illustrate applications to the analysis of algorithms that are playing a critical role in the evolution of our modern computational infrastructure. Improvements and additions in this new edition include Upgraded figures and code An all-new chapter introducing analytic combinatorics Simplified derivations via analytic combinatorics throughout The book’s thorough, self-contained coverage will help readers appreciate the field’s challenges, prepare them for advanced results—covered in their monograph Analytic Combinatorics and in Donald Knuth’s The Art of Computer Programming books—and provide the background they need to keep abreast of new research. "[Sedgewick and Flajolet] are not only worldwide leaders of the field, they also are masters of exposition. I am sure that every serious computer scientist will find this book rewarding in many ways." —From the Foreword by Donald E. Knuth
Analytic combinatorics aims to enable precise quantitative predictions of the properties of large combinatorial structures. The theory has emerged over recent decades as essential both for the analysis of algorithms and for the study of scientific models in many disciplines, including probability theory, statistical physics, computational biology, and information theory. With a careful combination of symbolic enumeration methods and complex analysis, drawing heavily on generating functions, results of sweeping generality emerge that can be applied in particular to fundamental structures such as permutations, sequences, strings, walks, paths, trees, graphs and maps. This account is the definitive treatment of the topic. The authors give full coverage of the underlying mathematics and a thorough treatment of both classical and modern applications of the theory. The text is complemented with exercises, examples, appendices and notes to aid understanding. The book can be used for an advanced undergraduate or a graduate course, or for self-study.
How do you distinguish a cat from a dog by their DNA? Did Shakespeare really write all of his plays? Pattern matching techniques can offer answers to these questions and to many others, from molecular biology, to telecommunications, to classifying Twitter content. This book for researchers and graduate students demonstrates the probabilistic approach to pattern matching, which predicts the performance of pattern matching algorithms with very high precision using analytic combinatorics and analytic information theory. Part I compiles known results of pattern matching problems via analytic methods. Part II focuses on applications to various data structures on words, such as digital trees, suffix trees, string complexity and string-based data compression. The authors use results and techniques from Part I and also introduce new methodology such as the Mellin transform and analytic depoissonization. More than 100 end-of-chapter problems help the reader to make the link between theory and practice.
This Brief presents the overarching framework in which each nation is developing its own cyber-security policy, and the unique position adopted by France. Modern informational crises have penetrated most societal arenas, from healthcare, politics, economics to the conduct of business and welfare. Witnessing a convergence between information warfare and the use of “fake news”, info-destabilization, cognitive warfare and cyberwar, this book brings a unique perspective on modern cyberwarfare campaigns, escalation and de-escalation of cyber-conflicts. As organizations are more and more dependent on information for the continuity and stability of their operations, they also become more vulnerable to cyber-destabilization, either genuine, or deliberate for the purpose of gaining geopolitical advantage, waging wars, conducting intellectual theft and a wide range of crimes. Subsequently, the regulation of cyberspace has grown into an international effort where public, private and sovereign interests often collide. By analyzing the particular case of France national strategy and capabilities, the authors investigate the difficulty of obtaining a global agreement on the regulation of cyber-warfare. A review of the motives for disagreement between parties suggests that the current regulation framework is not adapted to the current technological change in the cybersecurity domain. This book suggests a paradigm shift in handling and anchoring cyber-regulation into a new realm of behavioral and cognitive sciences, and their application to machine learning and cyber-defense.
Queues and stochastic networks are analyzed in this book with purely probabilistic methods. The purpose of these lectures is to show that general results from Markov processes, martingales or ergodic theory can be used directly to study the corresponding stochastic processes. Recent developments have shown that, instead of having ad-hoc methods, a better understanding of fundamental results on stochastic processes is crucial to study the complex behavior of stochastic networks. In this book, various aspects of these stochastic models are investigated in depth in an elementary way: Existence of equilibrium, characterization of stationary regimes, transient behaviors (rare events, hitting times) and critical regimes, etc. A simple presentation of stationary point processes and Palm measures is given. Scaling methods and functional limit theorems are a major theme of this book. In particular, a complete chapter is devoted to fluid limits of Markov processes.
Insights Into Low Molecular Weight and Cytotoxic Aggregates from in Vitro and Computer Experiments - Molecular Basis of Amyloid-Beta Protein Aggregation and Fibril Formation
Insights Into Low Molecular Weight and Cytotoxic Aggregates from in Vitro and Computer Experiments - Molecular Basis of Amyloid-Beta Protein Aggregation and Fibril Formation
Alzheimer's disease is the most common form of senile dementia, affecting more than 24 million people worldwide. It is characterised pathologically by abnormally high levels of neurofibrillary tangles resulting from the accumulation of tau protein in dead and dying neurons, and by elevated numbers of senile plaques in the cortex and hippocampus of the brain. The major component of senile plaques is a small protein of 39OCo43 amino acids called amyloid-? (A?). Thus far, no treatment has been shown to slow the progression of sporadic and familial Alzheimer's disease.A large body of evidence points, however, to the early A?-formed oligomers as the primary toxic species in Alzheimer's disease. A powerful strategy for developing pharmaceutical treatments against Alzheimer's is to elucidate the pathways of oligomer formation and determine the structures of the toxic aggregates.This book provides a panoramic view across recent in vitro and in vivo studies along with state-of-the-art computer simulations, designed to increase the readers' understanding of A? oligomerisation and fibril formation. At the same time, the book delves into the pathogenesis of familial and sporadic Alzheimer's disease at the atomic level of detail.Written by leading authors in their respective fields, this book will be valuable to all scientists working on Alzheimer's disease.
Despite growing interest, basic information on methods and models for mathematically analyzing algorithms has rarely been directly accessible to practitioners, researchers, or students. An Introduction to the Analysis of Algorithms, Second Edition, organizes and presents that knowledge, fully introducing primary techniques and results in the field. Robert Sedgewick and the late Philippe Flajolet have drawn from both classical mathematics and computer science, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures. They emphasize the mathematics needed to support scientific studies that can serve as the basis for predicting algorithm performance and for comparing different algorithms on the basis of performance. Techniques covered in the first half of the book include recurrences, generating functions, asymptotics, and analytic combinatorics. Structures studied in the second half of the book include permutations, trees, strings, tries, and mappings. Numerous examples are included throughout to illustrate applications to the analysis of algorithms that are playing a critical role in the evolution of our modern computational infrastructure. Improvements and additions in this new edition include Upgraded figures and code An all-new chapter introducing analytic combinatorics Simplified derivations via analytic combinatorics throughout The book’s thorough, self-contained coverage will help readers appreciate the field’s challenges, prepare them for advanced results—covered in their monograph Analytic Combinatorics and in Donald Knuth’s The Art of Computer Programming books—and provide the background they need to keep abreast of new research. "[Sedgewick and Flajolet] are not only worldwide leaders of the field, they also are masters of exposition. I am sure that every serious computer scientist will find this book rewarding in many ways." —From the Foreword by Donald E. Knuth
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