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Learning Automata and Stochastic Optimization (Lecture Notes in Control and Information Sciences)
Learning Automata and Stochastic Optimization (Lecture Notes in Control and Information Sciences)
In the last decades there has been a steadily growing need and interest in computational methods for solving optimization problems with or without constraints. They play an important role in many fields (chemistry, mechanic, electrical, economic, etc.). Optimization techniques have been gaining greater acceptance in many industrial applications....
Algorithms for Next Generation Networks (Computer Communications and Networks)
Algorithms for Next Generation Networks (Computer Communications and Networks)

Data networking now plays a major role in everyday life and new applications continue to appear at a blinding pace. Yet we still do not have a sound foundation for designing, evaluating and managing these networks.

This book covers topics at the intersection of algorithms and networking. It builds a complete picture of the current state...

Network-Based Distributed Planning Using Coevolutionary Algorithms (Intelligent Control and Intelligent Automation - Vol. 13)
Network-Based Distributed Planning Using Coevolutionary Algorithms (Intelligent Control and Intelligent Automation - Vol. 13)
In this book, efficient and scalable coevolutionary algorithms for distributed, network-based decision-making, which utilize objective functions are developed in a networked environment where internode communications are a primary factor in system performance.A theoretical foundation for this class of coevolutionary algorithms is introduced...
Stochastic Network Calculus (Computer Communications and Networks)
Stochastic Network Calculus (Computer Communications and Networks)
Network calculus, a theory dealing with queuing systems found in computer networks, focuses on performance guarantees. The development of an information theory for stochastic service-guarantee analysis has been identified as a grand challenge for future networking research. Towards that end, stochastic network calculus, the probabilistic version or...
Modeling with Stochastic Programming (Springer Series in Operations Research and Financial Engineering)
Modeling with Stochastic Programming (Springer Series in Operations Research and Financial Engineering)

While there are several texts on how to solve and analyze stochastic programs, this is the first text to address basic questions about how to model uncertainty, and how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This text would be suitable as a stand-alone or supplement for a second course in...

Petri Nets: Fundamental Models, Verification and Applications
Petri Nets: Fundamental Models, Verification and Applications

A Petri net is a mathematical representation of a network. This book first introduces the basic models including time and stochastic extensions, in particular place-transition and high level Petri nets. Their modeling and design capabilities are illustrated by a set of representations of interest in operating and communication systems. The...

Combinatorial Image Analysis: 12th International Workshop, IWCIA 2008, Buffalo, NY, USA, April 7-9, 2008, Proceedings
Combinatorial Image Analysis: 12th International Workshop, IWCIA 2008, Buffalo, NY, USA, April 7-9, 2008, Proceedings
This volume constitutes the refereed proceedings of the 12th International Workshop on Combinatorial Image Analysis, IWCIA 2008, held in Buffalo, NY, USA, in April 2008.

The 28 revised full papers and 10 revised poster papers presented were carefully reviewed and selected from 117 initial submissions. The papers are organized in topical...

Scaling, Fractals and Wavelets
Scaling, Fractals and Wavelets

Scaling is a mathematical transformation that enlarges or diminishes objects. The technique is used in a variety of areas, including finance and image processing. This book is organized around the notions of scaling phenomena and scale invariance. The various stochastic models commonly used to describe scaling ? self-similarity, long-range...

A First Course in Statistical Programming with R
A First Course in Statistical Programming with R

This text began as notes for a course in statistical computing for second year actuarial and statistical students at the University of Western Ontario. Both authors are interested in statistical computing, both as support for our other research and for its own sake. However, we have found that our students were not learning the right sort of...

Modelling and Control for Intelligent Industrial Systems: Adaptive Algorithms in Robotics and Industrial Engineering
Modelling and Control for Intelligent Industrial Systems: Adaptive Algorithms in Robotics and Industrial Engineering

Incorporating intelligence in industrial systems can help to increase productivity, cut-off production costs, and to improve working conditions and safety in industrial environments. This need has resulted in the rapid development of modeling and control methods for industrial systems and robots, of fault detection and isolation methods for...

A Measure Theoretical Approach to Quantum Stochastic Processes (Lecture Notes in Physics) (Volume 878)
A Measure Theoretical Approach to Quantum Stochastic Processes (Lecture Notes in Physics) (Volume 878)

This monograph takes as starting point that abstract quantum stochastic processes can be understood as a quantum field theory in one space and in one time coordinate. As a result it is appropriate to represent operators as power series of creation and annihilation operators in normal-ordered form, which can be achieved using classical measure...

Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information
Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information

In the context of systems and control, incomplete information refers to a dynamical system in which knowledge about the system states is limited due to the difficulties in modelling complexity in a quantitative way. The well-known types of incomplete information include parameter uncertainties and norm-bounded nonlinearities. Recently, in...

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