Genetic Algorithms for Applied CAD Problems

Jack Meredith and Scott Shafer abandon the traditional approach for operations management books and focus on business processes and spreadsheets to solve problems. They provide readers with an applied

Blending theoretical results with practical applications, this book provides an introduction to random matrix theory and shows how it can be used to tackle a variety of problems in wireless communications. The Stieltjes transform method, free probability theory, combinatoric approaches, deterministic equivalents and spectral analysis methods for statistical inference are all covered from a unique engineering perspective. Detailed mathematical derivations are presented throughout, with thorough explanation of the key results and all fundamental lemmas required for the reader to derive similar calculus on their own. These core theoretical concepts are then applied to a wide range of real-world problems in signal processing and wireless communications, including performance analysis of CDMA, MIMO and multi-cell networks, as well as signal detection and estimation in cognitive radio networks. The rigorous yet intuitive style helps demonstrate to students and researchers alike how to choose

This book provides a straightforward overview for every researcher interested in stochastic dynamic vehicle routing problems (SDVRPs). The book is written for both the applied researcher looking for s

This book presents an overview of the state of the art in the application of unsupervised algorithms to the study of undeciphered scripts. It shows how these algorithms can be applied to the Indus scr

This book explores how the method known as the partition method for a power series expansion, which has been developed by the author, can be applied to a host of previously intractable problems in mat

This book combines a solid theoretical background in linear algebra with practical algorithms for numerical solution of linear algebra problems. Developed from a number of courses taught repeatedly by

This book gives a reasonably self-contained account of a number of algorithmic problems and their solutions for linear algebraic groups. The theory underpinning the algorithms is described as well. To

The fundamental concept of Lebesgue integration provides a basis for approaching theoretical and applied problems in mathematics, engineering, physics and many other sciences.Lebesgue Integration pres

"This very informative book introduces classical and novel statistical methods that can be used by theoretical and applied biostatisticians to develop efficient solutions for real-world problems encou

Graphical models, a marriage between probability theory and graph theory, provide a natural tool for dealing with two problems that occur throughout applied mathematics and engineering--uncertainty an

This long-awaited two-volume book examines how the interplay of ideas and actions applied to environmental problems has laid the foundations for global environmental management. It looks at how ideas,

This long-awaited two-volume book examines how the interplay of ideas and actions applied to environmental problems has laid the foundations for global environmental management. It looks at how ideas,

This long-awaited two-volume book examines how the interplay of ideas and actions applied to environmental problems has laid the foundations for global environmental management. It looks at how ideas,

This long-awaited two-volume book examines how the interplay of ideas and actions applied to environmental problems has laid the foundations for global environmental management. It looks at how ideas,

Extension of time submissions are often made after a project has been severely delayed, when consequent problems may be unavoidable. However, if a proper submission is applied for as delays emerge, di

Provides a new and more realistic framework for describing the dynamics of non-linear systems. A number of issues arising in applied dynamical systems from the viewpoint of problems of phase space tra

Algorithmic graph theory has been expanding at an extremely rapid rate since the middle of the twentieth century, in parallel with the growth of computer science and the accompanying utilization of computers, where efficient algorithms have been a prime goal. This book presents material on developments on graph algorithms and related concepts that will be of value to both mathematicians and computer scientists, at a level suitable for graduate students, researchers and instructors. The fifteen expository chapters, written by acknowledged international experts on their subjects, focus on the application of algorithms to solve particular problems. All chapters were carefully edited to enhance readability and standardize the chapter structure as well as the terminology and notation. The editors provide basic background material in graph theory, and a chapter written by the book's Academic Consultant, Martin Charles Golumbic (University of Haifa, Israel), provides background material on al

This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and panel data. The book is oriented to the practitioner. A basic understanding of the linear regression model with matrix algebra is assumed. The text can be used for a microeconometrics course, typically a second-year economics PhD course; for data-oriented applied microeconometrics field courses; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their toolkit. Distinguishing features of the book include emphasis on nonlinear models and robust inference, simulation-based estimation, and problems of complex survey data. The book makes frequent use of numerical examples based on generated data to illustrate the key models and methods. More substantially, it systematically integrates into the text empirical illustrations based on s

Many machine learning algorithms require real-valued feature vectors of data instances as inputs. By projecting data into vector spaces, representation learning techniques have achieved promising performance in many areas such as computer vision and natural language processing. There is also a need to learn representations for discrete relational data, namely networks or graphs. Network Embedding (NE) aims at learning vector representations for each node or vertex in a network to encode the topologic structure. Due to its convincing performance and efficiency, NE has been widely applied in many network applications such as node classification and link prediction.This book provides a comprehensive introduction to the basic concepts, models, and applications of network representation learning (NRL). The book starts with an introduction to the background and rising of network embeddings as a general overview for readers. Then it introduces the development of NE techniques by presenting se

Topology optimization is a digital method for designing objects in order to achieve the best structural performance, sometimes in combination with other physical requirements. Topology optimization tools use mathematical algorithms, such as the finite element method and gradient computation, to generate designs based on desired characteristics and predetermined constraints. Initially a purely academic tool, topology optimization has advanced rapidly and is increasingly being applied to the design of a wide range of products and components, from furniture to spacecraft. To explore the potential and challenges of topology optimization, the National Academies of Sciences, Engineering, and Medicine hosted a two-day workshop on November 19-20, 2019, Exploiting Advanced Manufacturing Capabilities: Topology Optimization in Design. The workshop was organized around three main topics: how topology optimization can incorporate manufacturability along with functional design; challenges and opport

This is the second volume of a unique collection that brings together the best English-language problems created for students competing in the Computational Linguistics Olympiad. These problems are representative of the diverse areas presented in the competition and designed with three principles in mind:· To challenge the student analytically, without requiring any explicit knowledge or experience in linguistics or computer science;· To expose the student to the different kinds of reasoning required when encountering a new phenomenon in a language, both as a theoretical topic and as an applied problem;· To foster the natural curiosity students have about the workings of their own language, as well as to introduce them to the beauty and structure of other languages;· To learn about the models and techniques used by computers to understand human language.Aside from being a fun intellectual challenge, the Olympiad mimics the skills used by researchers and scholars in the field of computa

This is the first volume of a unique collection that brings together the best English-language problems created for students competing in the Computational Linguistics Olympiad. These problems are representative of the diverse areas presented in the competition and designed with three principles in mind:· To challenge the student analytically, without requiring any explicit knowledge or experience in linguistics or computer science;· To expose the student to the different kinds of reasoning required when encountering a new phenomenon in a language, both as a theoretical topic and as an applied problem;· To foster the natural curiosity students have about the workings of their own language, as well as to introduce them to the beauty and structure of other languages;· To learn about the models and techniques used by computers to understand human language. Aside from being a fun intellectual challenge, the Olympiad mimics the skills used by researchers and scholars in the field of computa

●ACTIONABLE AND MEASURABLE LEARNING OBJECTIVES EMPHASIZE IMPORTANT CONCEPTS. Newly added learning objectives guide students through the edition, calling attention to critical key points.●SOLID OVERVIEW PRESENTS BREADTH OF COMPUTER SCIENCE WITHOUT PROGRAMMING LANGUAGE SPECIFICS. The authors expertly present a language-independent, breadth-first introduction to computer science that includes coverage of today's hardware, software, and applications as well as a modern view of ethics.●UNIQUE APPROACH INTEGRATES TOPICS USING THE CONCEPT OF ALGORITHMS. Rather than simply present a large collection of seemingly random and unrelated topics, the authors tie the discipline of computer science together using a six-layer hierarchy that clearly demonstrates how the subjects in the book relate to each other. Student gain a clear understanding of the entire discipline of computer science that prepares them for future study in this field.●EXTENSIVE EXERCISES AND PROBLEMS PROVIDE NUMEROUS OPPORTUNITIES

This is a reissue of a classic originally published in 1970, with a new preface and some additional problems. Acton deals with a commonsense approach to numerical algorithms for the solution of equati

Algorithmic Number Theory provides a thorough introduction to the design and analysis of algorithms for problems from the theory of numbers. Although not an elementary textbook, it includes over 300 e