Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Markov Chains and Dependability Theory
Covers fundamental and applied results of Markov chain analysis for the evaluation of dependability metrics, for graduate students and researchers.
Markov Chains
Markov chains are a fundamental class of stochastic processes. They are widely used to solve problems in a large number of domains such as operational research, computer science, communication networks and manufacturing systems. The success of Markov chains is mainly due to their simplicity of use, the large number of available theoretical results and the quality of algorithms developed for the numerical evaluation of many metrics of interest. The author presents the theory of both discrete-time and continuous-time homogeneous Markov chains. He carefully examines the explosion phenomenon, the Kolmogorov equations, the convergence to equilibrium and the passage time distributions to a state a...
Markov Chains
Markov chains are a fundamental class of stochastic processes. They are widely used to solve problems in a large number of domains such as operational research, computer science, communication networks and manufacturing systems. The success of Markov chains is mainly due to their simplicity of use, the large number of available theoretical results and the quality of algorithms developed for the numerical evaluation of many metrics of interest. The author presents the theory of both discrete-time and continuous-time homogeneous Markov chains. He carefully examines the explosion phenomenon, the Kolmogorov equations, the convergence to equilibrium and the passage time distributions to a state a...
Analytical and Stochastic Modelling Techniques and Applications
This book constitutes the refereed proceedings of the 21st International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2014, held in Budapest, Hungary, in June/July 2014. The 18 papers presented were carefully reviewed and selected from 27 submissions. The papers discuss the latest developments in analytical, numerical and simulation algorithms for stochastic systems, including Markov processes, queueing networks, stochastic Petri nets, process algebras, game theory, etc.
Structural Information and Communication Complexity
This book constitutes the refereed post-conference proceedings of the 25th International Colloquium on Structural Information and Communication Complexity, SIROCCO 2018, held in Ma'ale HaHamisha, Israel, in June 2018. The 23 full papers and 8 short papers presented were carefully reviewed and selected from 47 submissions. They are devoted to the study of the interplay between structural knowledge, communications, and computing in decentralized systems of multiple communicating entities and cover a large range of topics.
Global Perspective for Competitive Enterprise, Economy and Ecology
Global Perspective for Competitive Enterprise, Economy and Ecology addresses the general theme of the Concurrent Engineering (CE) 2009 Conference – the need for global advancements in the areas of competitive enterprise, economy and ecology. The proceedings contain 84 papers, which vary from the theoretical and conceptual to the practical and industrial. The content of this volume reflects the genuine variety of issues related to current CE methods and phenomena. Global Perspective for Competitive Enterprise, Economy and Ecology will therefore enable researchers, industry practitioners, postgraduate students and advanced undergraduates to build their own view of the inherent problems and methods in CE.
Analytic Combinatorics for Multiple Object Tracking
The book shows that the analytic combinatorics (AC) method encodes the combinatorial problems of multiple object tracking—without information loss—into the derivatives of a generating function (GF). The book lays out an easy-to-follow path from theory to practice and includes salient AC application examples. Since GFs are not widely utilized amongst the tracking community, the book takes the reader from the basics of the subject to applications of theory starting from the simplest problem of single object tracking, and advancing chapter by chapter to more challenging multi-object tracking problems. Many established tracking filters (e.g., Bayes-Markov, PDA, JPDA, IPDA, JIPDA, CPHD, PHD, multi-Bernoulli, MBM, LMBM, and MHT) are derived in this manner with simplicity, economy, and considerable clarity. The AC method gives significant and fresh insights into the modeling assumptions of these filters and, thereby, also shows the potential utility of various approximation methods that are well established techniques in applied mathematics and physics, but are new to tracking. These unexplored possibilities are reviewed in the final chapter of the book.
