Introduction to Algorithms

This valuable source for graduate students and researchers provides a comprehensive introduction to current theories and applications in optimization methods and network models. Contributions to this

This easy-to-follow textbook is the second of 3 volumes which provide a modern, algorithmic introduction to digital image processing, designed to be used both by learners desiring a firm foundation on

Thisbook offers a comprehensive introduction to polymer rheology with a focus onthe viscoelastic characterization of polymeric materials. It contains variousnumerical algorithms for the processing of

This textbook offers an accessible introduction to the theory and numerics of approximation methods, combining classical topics of approximation with recent advances in mathematical signal processing,

Marking a distinct departure from the perspectives of frame theory and discrete transforms, this book provides a comprehensive mathematical and algorithmic introduction to wavelet theory. As such, it

This introduction to quantum algorithms is concise but comprehensive, covering many key algorithms. It is mathematically rigorous but requires minimal background and assumes no knowledge of quantum th

This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing termina

This book provides a general introduction to modern mathematical aspects in computing with multivariate polynomials and in solving algebraic systems. It presents the state of the art in several symbol

Kantardzic (computer engineering and science, U. of Louisville) offers students a single-volume introduction to the methods, tools, and algorithms in data mining that can also be used as a broad, if s

In To Will and To Do, twentieth-century French thinker Jacques Ellul presented his landmark theological contribution, yet the full text has never before been available in English. Incorporating recent insights on Ellul, and benefitting from the discovery of a lost manuscript, this new edition remedies this, combining a fresh translation of Volume One with a first English translation of Volume Two. Together, the two volumes constitute the first part of Ellul's planned four-part treatment of Christian ethics. In Volume One, Ellul examines the origin of the problem of Good and Evil, surveys the contemporary morality of Western society, and provocatively sketches the paradox of an impossible and yet necessary Christian ethics. In Volume Two, he carries this discussion forward, outlining the characteristics and conditions of Christian ethics, and analysing the relationship between ethics, the legal texts of the Bible. and dogmatic theology. He concludes by reimagining the theological use of

JSON has become a widely accepted and popular format for data due to its platform neutral nature, lightweight format, and its friendly structure for object oriented languages. JSON is being used every

What causes sprawl, and are there sensible solutions to its aggravating problems? Nozzi delivers an easy-to-follow introduction to sprawl's causes and offers common-sense solutions available to commu

In The Prosperity Matrix, you will discover the three intersecting circles that represent the three foundational areas of your life that, when cultivated and developed, set you up to enjoy sustainable

Programming Guide for Wearable Computing: Architecture, Algorithm and Examples gives expertise in proven techniques for writing the front end, middleware and back end software for the wearable computi

This book provides a computational perspective on partial order and lattice theory, focusing on algorithms and their complexity.Examines; posets, Dilworth’s theorem, merging algorithms, lattices, latt

This text provides an introduction to the mathematical modeling and subsequent optimization of vehicle propulsion systems and their supervisory control algorithms. It focuses on the minimization of fu

1 Computer Basics2 HTML and Web Pages3 The Internet and the Web4 JavaScript and Dynamic Web Pages5 JavaScript and User Interaction6 The History of Computers7 Functions and Randomness8 Algorithms and P

In this work we plan to revise the main techniques for enumeration algorithms and to show four examples of enumeration algorithms that can be applied to efficiently deal with some biological problems

The concept of 'shape' is at the heart of image processing and computer vision, yet researchers still have some way to go to replicate the human brain's ability to extrapolate meaning from the most ba

There are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve every computational problem. Nor are there silver bullets in algorithm analysis, as the most enlightening method for analyzing an algorithm often depends on the problem and the application. However, typical algorithms courses rely almost entirely on a single analysis framework, that of worst-case analysis, wherein an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which can be taught in lectures to beginning graduate students in theoretical computer science and machine learning.

This book offers an essential overview of computational conformal geometry applied to fundamental problems in specific engineering fields. It introduces readers to conformal geometry theory and discus

This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems. Though most of the new metaheuristic algorithms conside

Algorithmic design is not simply the use of computer to design architecture and objects. Algorithms allow designers to overcome the limitations of traditional CAD software and 3D modelers, reaching a

This comprehensive guide describes how evolutionary algorithms (EA) may be used to identify, model, and optimize day-to-day problems that arise for researchers in optimization and mobile networking. I

This user-friendly, engaging textbook makes the material accessible to graduate students and new researchers who wish to study the rapidly exploding area of computations with structured matrices and p

“Software Tools and Algorithms for Biological Systems" is composed of a collection of papers received in response to an announcement that was widely distributed to academicians and practitioners in th

This user-friendly, engaging textbook makes the material accessible to graduate students and new researchers who wish to study the rapidly exploding area of computations with structured matrices and p

With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for grad

Comprehensive Coverage of the New, Easy-to-Learn C#Although C, C++, Java, and Fortran are well-established programming languages, the relatively new C# is much easier to use for solving complex scient

There is a growing need for a more automated system of partitioning data sets into groups, or clusters. For example, digital libraries and the World Wide Web continue to grow exponentially, the ability to find useful information increasingly depends on the indexing infrastructure or search engine. Clustering techniques can be used to discover natural groups in data sets and to identify abstract structures that might reside there, without having any background knowledge of the characteristics of the data. Clustering has been used in a variety of areas, including computer vision, VLSI design, data mining, bio-informatics (gene expression analysis), and information retrieval, to name just a few. This book focuses on a few of the most important clustering algorithms, providing a detailed account of these major models in an information retrieval context. The beginning chapters introduce the classic algorithms in detail, while the later chapters describe clustering through divergences and sh

This is the first Visual Basic.NET book to provide a comprehensive discussion of the major data structures and algorithms. Here, instead of having to translate material on C++ or Java, the professional or student VB.NET programmer will find a tutorial on how to use data structures and algorithms and a reference for implementation using VB.NET for data structures and algorithms from the .NET Framework Class Library as well as those which must be developed by the programmer. In an object-oriented fashion, the author presents arrays and arraylists, linked lists, hash tables, dictionaries, trees, graphs, sorting and searching as well as more advanced algorithms, such as probabilistic algorithms and dynamic programming. His approach is very practical, for example using timing tests rather than Big O analysis to compare the performance of data structures and algorithms. This book can be used in both beginning and advanced computer programming courses that use the VB.NET language and, most im

This innovative book models pollution mitigation as a negative externality whilst also providing desirable and useful solutions, such as establishing the triangular equivalence relationship among the Lindahl equilibrium without transfers, the Nash bargaining solution with the payoffs of the Cournot-Nash equilibrium as the status quo point, and the social optimum under the Lindahl weights. By introducing programming algorithms to validate these relationships numerically, Zili Yang bridges the gap between analytical results and empirical modelling, ultimately solving the Lindahl equilibrium and hybrid Nash equilibria in the influential RICE model. This text demonstrates the complexity and variety of environment externality problems, ranging from mixed externality to correlated externalities to environmental externality under IRS and policy applications. Integrating theory, algorithms and applications in a comprehensive framework, The Environment and Externality will benefit scholars and

This innovative book models pollution mitigation as a negative externality whilst also providing desirable and useful solutions, such as establishing the triangular equivalence relationship among the Lindahl equilibrium without transfers, the Nash bargaining solution with the payoffs of the Cournot-Nash equilibrium as the status quo point, and the social optimum under the Lindahl weights. By introducing programming algorithms to validate these relationships numerically, Zili Yang bridges the gap between analytical results and empirical modelling, ultimately solving the Lindahl equilibrium and hybrid Nash equilibria in the influential RICE model. This text demonstrates the complexity and variety of environment externality problems, ranging from mixed externality to correlated externalities to environmental externality under IRS and policy applications. Integrating theory, algorithms and applications in a comprehensive framework, The Environment and Externality will benefit scholars and

A new, intuitive approach to machine learning, covering fundamental concepts and real-world applications, with practical MATLAB-based exercises.

Several geometric problems can be formulated in terms of the arrangement of a collection of curves in a plane, which has made this one of the most widely studied topics in computational geometry. This book, first published in 1991, presents a study of various problems related to arrangements of lines, segments, or curves in the plane. The first problem is a proof of almost tight bounds on the length of (n,s)-Davenport–Schinzel sequences, a technique for obtaining optimal bounds for numerous algorithmic problems. Then the intersection problem is treated. The final problem is improving the efficiency of partitioning algorithms, particularly those used to construct spanning trees with low stabbing numbers, a very versatile tool in solving geometric problems. A number of applications are also discussed. Researchers in computational and combinatorial geometry should find much to interest them in this book.

The starting point in the formulation of any numerical problem is to take an intuitive idea about the problem in question and to translate it into precise mathematical language. This book provides step-by-step descriptions of how to formulate numerical problems and develops techniques for solving them. A number of engineering case studies motivate the development of efficient algorithms that involve, in some cases, transformation of the problem from its initial formulation into a more tractable form. Five general problem classes are considered: linear systems of equations, non-linear systems of equations, unconstrained optimization, equality-constrained optimization and inequality-constrained optimization. The book contains many worked examples and homework exercises and is suitable for students of engineering or operations research taking courses in optimization. Supplementary material including solutions, lecture slides and appendices are available online at www.cambridge.org/9780521

This volume is devoted to Analysis of Algorithms, a field that Knuth founded and still considers his main life's work.

Steganography, the art of hiding of information in apparently innocuous objects or images, is a field with a rich heritage, and an area of rapid current development. This clear, self-contained guide shows you how to understand the building blocks of covert communication in digital media files and how to apply the techniques in practice, including those of steganalysis, the detection of steganography. Assuming only a basic knowledge in calculus and statistics, the book blends the various strands of steganography, including information theory, coding, signal estimation and detection, and statistical signal processing. Experiments on real media files demonstrate the performance of the techniques in real life, and most techniques are supplied with pseudo-code, making it easy to implement the algorithms. The book is ideal for students taking courses on steganography and information hiding, and is also a useful reference for engineers and practitioners working in media security and informati