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Computer Science and Intelligent Systems

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This text offers a comprehensive treatment of VHDL and its applications to the design and simulation of real, industry-standard circuits. It focuses on the use of VHDL rather than solely on the language, showing why and how certain types of circuits are inferred from the language constructs and how any of the four simulation categories can be implemented. It makes a rigorous distinction between VHDL for synthesis and VHDL for simulation.

Designing Sound teaches students and professional sound designers to understand and create sound effects starting from nothing. Its thesis is that any sound can be generated from first principles, guided by analysis and synthesis. The text takes a practitioner's perspective, exploring the basic principles of making ordinary, everyday sounds using an easily accessed free software. Readers use the Pure Data (Pd) language to construct sound objects, which are more flexible and useful than recordings.

Implementing and Evaluating Search Engines

Information retrieval is the foundation for modern search engines. This text offers an introduction to the core topics underlying modern search technologies, including algorithms, data structures, indexing, retrieval, and evaluation. The emphasis is on implementation and experimentation; each chapter includes exercises and suggestions for student projects. Wumpus—a multiuser open-source information retrieval system developed by one of the authors and available online—provides model implementations and a basis for student work.

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts.

Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming.

Scheme is a general-purpose programming language, descended from Algol and Lisp, widely used in computing education and research and a broad range of industrial applications. This thoroughly updated edition of The Scheme Programming Language provides an introduction to Scheme and a definitive reference for standard Scheme, presented in a clear and concise manner.

Principles and Techniques

Most tasks require a person or an automated system to reason—to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible.

This text is the first comprehensive presentation of reduction semantics in one volume; it also introduces the first reliable and easy-to-use tool set for such forms of semantics. Software engineers have long known that automatic tool support is critical for rapid prototyping and modeling, and this book is addressed to the working semantics engineer (graduate student or professional language designer). The book comes with a prototyping tool suite to develop, explore, test, debug, and publish semantic models of programming languages.

This text is a guide to the foundations of method engineering, a developing field concerned with the definition of techniques for designing software systems. The approach is based on metamodeling, the construction of a model about a collection of other models. The book applies the metamodeling approach in five case studies, each describing a solution to a problem in a specific domain. Suitable for classroom use, the book is also useful as a reference for practitioners.

Theories, Methods, and Technologies

New approaches to artificial intelligence spring from the idea that intelligence emerges as much from cells, bodies, and societies as it does from evolution, development, and learning. Traditionally, artificial intelligence has been concerned with reproducing the abilities of human brains; newer approaches take inspiration from a wider range of biological structures that that are capable of autonomous self-organization.

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