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Introduction to Parallel Processing
THE CONTEXT OF PARALLEL PROCESSING The field of digital computer architecture has grown explosively in the past two decades. Through a steady stream of experimental research, tool-building efforts, and theoretical studies, the design of an instruction-set architecture, once considered an art, has been transformed into one of the most quantitative branches of computer technology. At the same time, better understanding of various forms of concurrency, from standard pipelining to massive parallelism, and invention of architectural structures to support a reasonably efficient and user-friendly programming model for such systems, has allowed hardware performance to continue its exponential growth. This trend is expected to continue in the near future. This explosive growth, linked with the expectation that performance will continue its exponential rise with each new generation of hardware and that (in stark contrast to software) computer hardware will function correctly as soon as it comes off the assembly line, has its down side. It has led to unprecedented hardware complexity and almost intolerable dev- opment costs. The challenge facing current and future computer designers is to institute simplicity where we now have complexity; to use fundamental theories being developed in this area to gain performance and ease-of-use benefits from simpler circuits; to understand the interplay between technological capabilities and limitations, on the one hand, and design decisions based on user and application requirements on the other.
R 6,091.81
R 2,741.92
Introduction to Bioinformatics and Clinical Scientific Computing
This textbook provides an introduction to computer science theory, informatics best practice, and the standards and legislation that apply to computing in a healthcare environment. It delivers an accessible discussion of databases (construction, interrogation and maintenance); networking (design and low-level application); programming (best practice rather than the specifics of any one language – design, maintenance, safety). It can be used to accompany the NHS Modernising Scientific Careers syllabus. It is also targeted towards those creating software rather than those using it, particularly computer scientists working in healthcare, specifically those in or close to the Physical Sciences, including radiotherapy, nuclear medicine, and equipment management and those working with genomics and health informatics. Features Combines all topics into one comprehensive introduction. Explores practical applications of theory to healthcare. Can be used to accompany the NHS Modernising Scientific Careers syllabus.
R 5,165.00
Introduction to Probability with R
Based on a popular course taught by the late Gian-Carlo Rota of MIT, with many new topics covered as well, Introduction to Probability with R presents R programs and animations to provide an intuitive yet rigorous understanding of how to model natural phenomena from a probabilistic point of view. Although the R programs are small in length, they are just as sophisticated and powerful as longer programs in other languages. This brevity makes it easy for students to become proficient in R.This calculus-based introduction organizes the material around key themes. One of the most important themes centers on viewing probability as a way to look at the world, helping students think and reason probabilistically. The text also shows how to combine and link stochastic processes to form more complex processes that are better models of natural phenomena. In addition, it presents a unified treatment of transforms, such as Laplace, Fourier, and z; the foundations of fundamental stochastic processes using entropy and information; and an introduction to Markov chains from various viewpoints. Each chapter includes a short biographical note about a contributor to probability theory, exercises, and selected answers.The book has an accompanying website with more information.
R 2,853.29
Introduction to Image Classification
Image classification is a critical component in computer vision tasks and has numerous applications. Traditional methods for image classification involves feature extraction and classification in feature space. Current state-of-the-art methods utilize end-to-end learning with deep neural networks, where feature extraction and classification are integrated into the model. Understanding traditional image classification is important because many of its design concepts directly correspond to components of a neural networks. This knowledge can help demystify the behavior of these networks, which may seem opaque at first sight.The book starts from introducing methods for model-driven feature extraction and classification, including basic computer vision techniques for extracting high-level semantics from images. A brief overview of probabilistic classification with generative and discriminative classifiers is then provided. Next, neural networks are presented as a means to learn a classification model directly from labeled sample images, with individual components of the network discussed. The relationships between network components and those of a traditional designed model are explored, and different concepts for regularizing model training are explained. Finally, various methods for analyzing what a network has learned are covered in the closing section of the book.The topic of image classification is presented as a thoroughly curated sequence of steps that gradually increase understanding of the working of a fully trainable classifier. Practical exercises in Python/Keras/Tensorflow have been designed to allow for experimental exploration of these concepts. In each chapter, suitable functions from Python modules are briefly introduced to provide students with the necessary tools to conduct these experiments.
R 3,114.00
Introduction to Optimization
This undergraduate textbook introduces students of science and engineering to the fascinating field of optimization. It is a unique book that brings together the subfields of mathematical programming, variational calculus, and optimal control, thus giving students an overall view of all aspects of optimization in a single reference. As a primer on optimization, its main goal is to provide a succinct and accessible introduction to linear programming, nonlinear programming, numerical optimization algorithms, variational problems, dynamic programming, and optimal control. Prerequisites have been kept to a minimum, although a basic knowledge of calculus, linear algebra, and differential equations is assumed.
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R 3,847.00
Introduction to Computational Engineering with MATLAB®
Introduction to Computational Engineering with MATLAB® aims to teach readers how to use MATLAB programming to solve numerical engineering problems. The book focuses on computational engineering with the objective of helping engineering students improve their numerical problem-solving skills. The book cuts a middle path between undergraduate texts that simply focus on programming and advanced mathematical texts that skip over foundational concepts, feature cryptic mathematical expressions, and do not provide sufficient support for novices.Although this book covers some advanced topics, readers do not need prior computer programming experience or an advanced mathematical background. Instead, the focus is on learning how to leverage the computer and software environment to do the hard work. The problem areas discussed are related to data-driven engineering, statistics, linear algebra, and numerical methods. Some example problems discussed touch on robotics, control systems, and machine learning.Features:Demonstrates through algorithms and code segments how numeric problems are solved with only a few lines of MATLAB code Quickly teaches students the basics and gets them started programming interesting problems as soon as possibleNo prior computer programming experience or advanced math skills required Suitable for students at undergraduate level who have prior knowledge of college algebra, trigonometry, and are enrolled in Calculus IMATLAB script files, functions, and datasets used in examples are available for download from http://www.routledge.com/9781032221410.
R 3,850.76
Hands-On Introduction to LabVIEW for Scientists and Engineers
Hands-On Introduction to LaVIEW for Scientists and Engineers provides a learn-by-doing approach to acquiring the computer-based skills used daily in experimental work. The book is not the typical manual-like presentation of LabVIEW. Rather, Hands-On Introduction to LabVIEW guides students through using this powerful laboratory tool to carry out interesting and relevant projects. Readers, who are assumed to have no prior computer programming orLabVIEW experience, begin writing meaningful programs in the first few pages. After learning through experience, readers can master the skills needed to carry out effective experiments.
R 2,589.00
Introduction to Data Technologies
Providing key information on how to work with research data, Introduction to Data Technologies presents ideas and techniques for performing critical, behind-the-scenes tasks that take up so much time and effort yet typically receive little attention in formal education. With a focus on computational tools, the book shows readers how to improve their awareness of what tasks can be achieved and describes the correct approach to perform these tasks. Practical examples demonstrate the most important pointsThe author first discusses how to write computer code using HTML as a concrete example. He then covers a variety of data storage topics, including different file formats, XML, and the structure and design issues of relational databases. After illustrating how to extract data from a relational database using SQL, the book presents tools and techniques for searching, sorting, tabulating, and manipulating data. It also introduces some very basic programming concepts as well as the R language for statistical computing. Each of these topics has supporting chapters that offer reference material on HTML, CSS, XML, DTD, SQL, R, and regular expressions.One-stop shop of introductory computing information Written by a member of the R Development Core Team, this resource shows readers how to apply data technologies to tasks within a research setting. Collecting material otherwise scattered across many books and the web, it explores how to publish information via the web, how to access information stored in different formats, and how to write small programs to automate simple, repetitive tasks.
R 12,346.23
Introduction to Cryptography with Mathematical Foundations and Computer Implementations
From the exciting history of its development in ancient times to the present day, Introduction to Cryptography with Mathematical Foundations and Computer Implementations provides a focused tour of the central concepts of cryptography. Rather than present an encyclopedic treatment of topics in cryptography, it delineates cryptographic concepts in chronological order, developing the mathematics as needed. Written in an engaging yet rigorous style, each chapter introduces important concepts with clear definitions and theorems. Numerous examples explain key points while figures and tables help illustrate more difficult or subtle concepts. Each chapter is punctuated with "Exercises for the Reader;" complete solutions for these are included in an appendix. Carefully crafted exercise sets are also provided at the end of each chapter, and detailed solutions to most odd-numbered exercises can be found in a designated appendix. The computer implementation section at the end of every chapter guides students through the process of writing their own programs. A supporting website provides an extensive set of sample programs as well as downloadable platform-independent applet pages for some core programs and algorithms.As the reliance on cryptography by business, government, and industry continues and new technologies for transferring data become available, cryptography plays a permanent, important role in day-to-day operations. This self-contained sophomore-level text traces the evolution of the field, from its origins through present-day cryptosystems, including public key cryptography and elliptic curve cryptography.
R 6,803.03
R 807.62
Introduction to Computational Engineering with MATLAB®
Introduction to Computational Engineering with MATLAB® aims to teach readers how to use MATLAB programming to solve numerical engineering problems. The book focuses on computational engineering with the objective of helping engineering students improve their numerical problem-solving skills. The book cuts a middle path between undergraduate texts that simply focus on programming and advanced mathematical texts that skip over foundational concepts, feature cryptic mathematical expressions, and do not provide sufficient support for novices.Although this book covers some advanced topics, readers do not need prior computer programming experience or an advanced mathematical background. Instead, the focus is on learning how to leverage the computer and software environment to do the hard work. The problem areas discussed are related to data-driven engineering, statistics, linear algebra, and numerical methods. Some example problems discussed touch on robotics, control systems, and machine learning.Features:Demonstrates through algorithms and code segments how numeric problems are solved with only a few lines of MATLAB code Quickly teaches students the basics and gets them started programming interesting problems as soon as possibleNo prior computer programming experience or advanced math skills required Suitable for students at undergraduate level who have prior knowledge of college algebra, trigonometry, and are enrolled in Calculus IMATLAB script files, functions, and datasets used in examples are available for download from http://www.routledge.com/9781032221410.
R 9,974.18
R 761.00
Introduction to Game Development Using Processing
This book will guide you through the basic game development process, covering game development topics including graphics, sound, artificial intelligence, animation, game engines, Web-based games, etc. Real games will be created, and significant parts of a game engine will be built and made available for download. The companion DVD will contain example code, games, and color figures. Processing is a free, graphics-oriented language that provides the basic functionality needed for building games and runs on all major platforms. Moreover, it allows games to be built for desktop computers, HTML 5, and Android. eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at info@merclearning.com.Features:Teaches basic game development including graphics, sound, artificial intelligence, animation, game engines, Web-based games, and moreCreate a small collection of complete computer games developed throughout the bookUses Processing, a free, downloadable platform with a frame by frame display scheme that is perfect for computer games
R 1,139.00
R 1,371.00
Introduction to Public Health Program Planning
Written to provide students with the essential program planning skills that they'll need in public health practice, Introduction to Public Health Program Planning offers an accessible and engaging approach to the program planning process. Divided into 3 parts, Introduction to Public Health Program Planning begins with an introduction to the basics of planning, health determinants, and behaviors. It then offers in-depth discussion of the generic planning phases - from assessing needs and planning to implementing and evaluation. The third section explores the four most commonly used planning frameworks, along with three additional planning frameworks that address specific health issues. A final chapter offers guidance on choosing a planning framework.Key Features:- Chapter-opening analogies to real-life situations help demystify chapter content and ease student understanding to chapter material.- Commonly used planning frameworks, including PRECEDE-PROCEED, MAPP, MAP-IT, and Intervention Mapping are discussed in detail in separate chapters that also include step-by-step instruction for their use.- End-of chapter activities that link to journal articles demonstrate how the material covered is applied in a practice setting.- Figures and tables provide visual examples that clarify and expand upon chapter material.- Navigate eBook Access (included with each new print text) enables students to read their digital textbook online or offline, on computers, tablets, and mobile devices.
R 2,005.00
Introduction to Statistics and Data Analysis
Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference.The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.
R 4,096.79
Introduction to Probability with R
Based on a popular course taught by the late Gian-Carlo Rota of MIT, with many new topics covered as well, Introduction to Probability with R presents R programs and animations to provide an intuitive yet rigorous understanding of how to model natural phenomena from a probabilistic point of view. Although the R programs are small in length, they are just as sophisticated and powerful as longer programs in other languages. This brevity makes it easy for students to become proficient in R. This calculus-based introduction organizes the material around key themes. One of the most important themes centers on viewing probability as a way to look at the world, helping students think and reason probabilistically. The text also shows how to combine and link stochastic processes to form more complex processes that are better models of natural phenomena. In addition, it presents a unified treatment of transforms, such as Laplace, Fourier, and z; the foundations of fundamental stochastic processes using entropy and information; and an introduction to Markov chains from various viewpoints. Each chapter includes a short biographical note about a contributor to probability theory, exercises, and selected answers. The book has an accompanying website with more information.
R 7,593.79
R 815.31
Short Introduction to Intuitionistic Logic
Intuitionistic logic is presented here as part of familiar classical logic which allows mechanical extraction of programs from proofs. to make the material more accessible, basic techniques are presented first for propositional logic; Part II contains extensions to predicate logic. This material provides an introduction and a safe background for reading research literature in logic and computer science as well as advanced monographs. Readers are assumed to be familiar with basic notions of first order logic. One device for making this book short was inventing new proofs of several theorems. The presentation is based on natural deduction. The topics include programming interpretation of intuitionistic logic by simply typed lambda-calculus (Curry-Howard isomorphism), negative translation of classical into intuitionistic logic, normalization of natural deductions, applications to category theory, Kripke models, algebraic and topological semantics, proof-search methods, interpolation theorem. The text developed from materal for several courses taught at Stanford University in 1992-1999.
R 3,820.98
Introduction to Embedded System Design Using Field Programmable Gate Arrays
"Introduction to Embedded System Design Using Field Programmable Gate Arrays" provides a starting point for the use of field programmable gate arrays in the design of embedded systems. The text considers a hypothetical robot controller as an embedded application and weaves around it related concepts of FPGA-based digital design. The book details: use of FPGA vis-à-vis general purpose processor and microcontroller; design using Verilog hardware description language; digital design synthesis using Verilog and Xilinx® SpartanTM 3 FPGA; FPGA-based embedded processors and peripherals; overview of serial data communications and signal conditioning using FPGA; FPGA-based motor drive controllers; and prototyping digital systems using FPGA.The book is a good introductory text for FPGA-based design for both students and digital systems designers. Its end-of-chapter exercises and frequent use of example can be used for teaching or for self-study.
R 3,016.87
Introduction to Fuzzy Linear Programming Problems
The book presents a snapshot of the state of the art in the field of fully fuzzy linear programming. The main focus is on showing current methods for finding the fuzzy optimal solution of fully fuzzy linear programming problems in which all the parameters and decision variables are represented by non-negative fuzzy numbers. It presents new methods developed by the authors, as well as existing methods developed by others, and their application to real-world problems, including fuzzy transportation problems. Moreover, it compares the outcomes of the different methods and discusses their advantages/disadvantages. As the first work to collect at one place the most important methods for solving fuzzy linear programming problems, the book represents a useful reference guide for students and researchers, providing them with the necessary theoretical and practical knowledge to deal with linear programming problems under uncertainty.
R 3,010.42
R 9,122.14
Introduction to Bioinformatics
Active, accessible, and assuming no prior knowledge: the ideal text for biologists encountering bioinformatics for the first time.A vast amount of biological information about a wide range of species has become available in recent years as technological advances have significantly reduced the time it takes to sequence a genome or determine a novel protein structure. This text describes how bioinformatics can be used as a powerful set of tools for retrieving and analysing this biological data, and how bioinformatics can be applied to a wide range of disciplines such as molecular biology, medicine, biotechnology, forensicscience and anthropology.Fully revised and updated, the fifth edition of Introduction to Bioinformatics contains a host of new material including new content on next generation sequencing, function prediction, sequence assembly, epigenomics, the bioinformatics of gene editing, and the effects of single nucleotide variants.Written primarily for a biological audience without a detailed prior knowledge of programming, this book is the perfect introduction to the field of bioinformatics, providing friendly guidance and advice on how to use various methods and techniques. Furthermore, frequent examples, self-test questions, problems, and exercises are incorporated throughout the text to encourage self-directed learning.
R 4,531.00
Computational Physics - A Practical Introduction to Computational Physics and Scientific Computing (Using C++), Vol. I
This book is an introduction to the computational methods used in physics and other related scientific fields. It is addressed to an audience that has already been exposed to the introductory level of college physics, usually taught during the first two years of an undergraduate program in science and engineering. It assumes no prior knowledge of numerical analysis, programming or computers and teaches whatever is necessary for the solution of the problems addressed in the text. C++ is used for programming the core programs and data analysis is performed using the powerful tools of the GNU/Linux environment. All the necessary software is open source and freely available. The book starts with very simple problems in particle motion and ends with an in-depth discussion of advanced techniques used in Monte Carlo simulations in statistical mechanics. The level of instruction rises slowly, while discussing problems like the diffusion equation, electrostatics on the plane, quantum mechanics and random walks.
R 1,283.99
Introduction to Digital Communications
Master the fundamentals of digital communications systems with this accessible and hands-on introductory textbook, carefully interweaving theory and practice. The just-in-time approach introduces essential background as needed, keeping academic theory firmly linked to practical applications. The example-led teaching frames key concepts in the context of real-world systems, such as 5G, WiFi, and GPS. Stark provides foundational material on the trade-offs between energy and bandwidth efficiency, giving students a solid grounding in the fundamental challenges of designing digital communications systems. Features include over 300 illustrative figures, 80 examples, and 130 end-of-chapter problems to reinforce student understanding, with solutions for instructors. Accompanied online by lecture slides, computational MATLAB® and Python resources, and supporting data sets, this is the ideal introduction to digital communications for senior undergraduate and graduate students in electrical engineering.
R 4,341.41
Introduction to Econophysics
Econophysics explores the parallels between physics and economics and is an exciting topic that is attracting increasing attention. However there is a lack of literature that explains the topic from a broad perspective. This book introduces advanced undergraduates and graduate students in physics and engineering to the topic from this outlook, and is accompanied by rigorous mathematics which ensures that this will also be a good guide for established researchers in the field as well as researchers from other fields, such as mathematics and statistics, who are interested in the topic.Key features: Presents a multidisciplinary approach that will be of interest to students and researchers from physics, engineering, mathematics, statistics, and other physical sciences Accompanied by Python code with further learning opportunities, available for readers to download from the CRC Press website. Accessible to both students and researchersCarlo R. da Cunha is an associate professor of physics and engineering physics at the Universidade Federal do Rio Grande do Sul (Brazil) and has been since 2011. Dr. da Cunha received his M.Sc. Degree from the West Virginia University in 2001 and his Ph.D. degree from Arizona State University in 2005. He was a postdoctoral researcher at McGill University in Canada in 2006 and an assistant professor of engineering at the University Federal de Santa Catarina between 2007 and 2011. He has been a guest professor at the Technische Universität Wien (Austria), Chiba University (Japan) and Arizona State University (US). His research revolves around the physics of complex systems where he has been drawing parallels between physical and economic systems from quantum to social levels.To access additional resources, such as python code, please take a look here.
R 2,839.48
Introduction to High Performance Computing for Scientists and Engineers
Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. From working in a scientific computing center, the authors gained a unique perspective on the requirements and attitudes of users as well as manufacturers of parallel computers.The text first introduces the architecture of modern cache-based microprocessors and discusses their inherent performance limitations, before describing general optimization strategies for serial code on cache-based architectures. It next covers shared- and distributed-memory parallel computer architectures and the most relevant network topologies. After discussing parallel computing on a theoretical level, the authors show how to avoid or ameliorate typical performance problems connected with OpenMP. They then present cache-coherent nonuniform memory access (ccNUMA) optimization techniques, examine distributed-memory parallel programming with message passing interface (MPI), and explain how to write efficient MPI code. The final chapter focuses on hybrid programming with MPI and OpenMP.Users of high performance computers often have no idea what factors limit time to solution and whether it makes sense to think about optimization at all. This book facilitates an intuitive understanding of performance limitations without relying on heavy computer science knowledge. It also prepares readers for studying more advanced literature.Read about the authors’ recent honor: Informatics Europe Curriculum Best Practices Award for Parallelism and Concurrency
R 4,249.00
Introduction to Mathematical Modeling
Introduction to Mathematical Modeling helps students master the processes used by scientists and engineers to model real-world problems, including the challenges posed by space exploration, climate change, energy sustainability, chaotic dynamical systems and random processes.Primarily intended for students with a working knowledge of calculus but minimal training in computer programming in a first course on modeling, the more advanced topics in the book are also useful for advanced undergraduate and graduate students seeking to get to grips with the analytical, numerical, and visual aspects of mathematical modeling, as well as the approximations and abstractions needed for the creation of a viable model.
R 2,878.03
Introduction to Fuzzy Logic using MATLAB
This book provides a broad-ranging, but detailed overview of the basics of Fuzzy Logic. The fundamentals of Fuzzy Logic are discussed in detail, and illustrated with various solved examples. The book also deals with applications of Fuzzy Logic, to help readers more fully understand the concepts involved. Solutions to the problems are programmed using MATLAB 6.0, with simulated results. The MATLAB Fuzzy Logic toolbox is provided for easy reference.
R 6,024.80
Introduction to Game Physics with Box2D
Written by a pioneer of game development in academia, Introduction to Game Physics with Box2D covers the theory and practice of 2D game physics in a relaxed and entertaining yet instructional style. It offers a cohesive treatment of the topics and code involved in programming the physics for 2D video games. Focusing on writing elementary game physics code, the first half of the book helps you grasp the challenges of programming game physics from scratch, without libraries or outside help. It examines the mathematical foundation of game physics and illustrates how it is applied in practice through coding examples. The second half of the book shows you how to use Box2D, a popular open source 2D game physics engine. A companion website provides supplementary material, including source code and videos.This book helps you become a capable 2D game physics programmer through its presentation of both the theory and applications of 2D game physics. After reading the book and experimenting with the code samples, you will understand the basics of 2D game physics and know how to use Box2D to make a 2D physics-based game.
R 3,705.64
Introduction to Cryptography
This book explains the basic methods of modern cryptography. It is written for readers with only basic mathematical knowledge who are interested in modern cryptographic algorithms and their mathematical foundation. Several exercises are included following each chapter. From the reviews: "Gives a clear and systematic introduction into the subject whose popularity is ever increasing, and can be recommended to all who would like to learn about cryptography." --ZENTRALBLATT MATH
R 2,238.68
Introduction to Logic
Originally published in 1969. This book is for undergraduates whether specializing in philosophy or not. It assumes no previous knowledge of logic but aims to show how logical notions arise from, or are abstracted from, everyday discourse, whether technical or non-technical. It sets out a knowledge of principles and, while not historical, gives an account of the reasons for which modern systems have emerged from the traditional syllogistic logic, demonstrating how certain central ideas have developed. The text explains the connections between everyday reasoning and formal logic and works up to a brief sketch of systems of propositional calculus and predicate-calculus, using both the axiomatic method and the method of natural deduction. It provides a self-contained introduction but for those who intend to study the subject further it contains many suggestions and a sound basis for more advanced study.
R 6,670.62
Introduction to Physical Chemistry
The third edition of this text has been completely rewritten and revised. It is intended for first- and second-year undergraduates in chemistry taking physical chemistry courses, and for undergraduates in other science and engineering subjects that require an understanding of chemistry. The author gives more attention to the solid and liquid states than is found in other texts on this subject, and introduces topics such as computer simulation and quasicrystals. Each chapter concludes with a set of problems, to which there are solution notes, designed to lead the reader to familiarity with the subject and its application in new situations. Computer programs designed to assist the reader are downloadable from the World Wide Web, from the time of publication. Detailed solutions to the problems will also be available via the World Wide Web. See http://www.cup.cam.ac.uk/stm/laddsolutions.htm. This modern text on physical chemistry will be of interest to undergraduate students in chemistry and also students in other areas of science and engineering requiring a familiarity with the subject.
R 5,143.00
R 587.00
Introduction to Error Correcting Codes with Applications
5. 2 Rings and Ideals 148 5. 3 Ideals and Cyclic Subspaces 152 5. 4 Generator Matrices and Parity-Check Matrices 159 5. 5 Encoding Cyclic Codest 163 5. 6 Syndromes and Simple Decoding Procedures 168 5. 7 Burst Error Correcting 175 5. 8 Finite Fields and Factoring xn-l over GF(q) 181 5. 9 Another Method for Factoring xn-l over GF(q)t 187 5. 10 Exercises 193 Chapter 6 BCH Codes and Bounds for Cyclic Codes 6. 1 Introduction 201 6. 2 BCH Codes and the BCH Bound 205 6. 3 Bounds for Cyclic Codest 210 6. 4 Decoding BCH Codes 215 6. 5 Linearized Polynomials and Finding Roots of Polynomialst 224 6. 6 Exercises 231 Chapter 7 Error Correction Techniques and Digital Audio Recording 7. 1 Introduction 237 7. 2 Reed-Solomon Codes 237 7. 3 Channel Erasures 240 7. 4 BCH Decoding with Erasures 244 7. 5 Interleaving 250 7. 6 Error Correction and Digital Audio Recording 256 7.
R 1,557.71
Gentle Introduction to Scientific Computing
Scientific Computation has established itself as a stand-alone area of knowledge at the borderline between computer science and applied mathematics. Nonetheless, its interdisciplinary character cannot be denied: its methodologies are increasingly used in a wide variety of branches of science and engineering.A Gentle Introduction to Scientific Computing intends to serve a very broad audience of college students across a variety of disciplines. It aims to expose its readers to some of the basic tools and techniques used in computational science, with a view to helping them understand what happens "behind the scenes" when simple tools such as solving equations, plotting and interpolation are used.To make the book as practical as possible, the authors explore their subject both from a theoretical, mathematical perspective and from an implementation-driven, programming perspective.FeaturesMiddle-ground approach between theory and implementation.Suitable reading for a broad range of students in STEM disciplines. Could be used as the primary text for a first course in scientific computing.Introduces mathematics majors, without any prior computer science exposure, to numerical methods.All mathematical knowledge needed beyond Calculus (together with the most widely used Calculus notation and concepts) is introduced in the text to make it self-contained. The erratum document for A Gentle Introduction to Scientific Computing can be accessed here.
R 5,642.28
R 1,286.06
R 965.00
Introduction to Learning Classifier Systems
This accessible introduction shows the reader how to understand, implement, adapt, and apply Learning Classifier Systems (LCSs) to interesting and difficult problems. The text builds an understanding from basic ideas and concepts. The authors first explore learning through environment interaction, and then walk through the components of LCS that form this rule-based evolutionary algorithm. The applicability and adaptability of these methods is highlighted by providing descriptions of common methodological alternatives for different components that are suited to different types of problems from data mining to autonomous robotics. The authors have also paired exercises and a simple educational LCS (eLCS) algorithm (implemented in Python) with this book. It is suitable for courses or self-study by advanced undergraduate and postgraduate students in subjects such as Computer Science, Engineering, Bioinformatics, and Cybernetics, and by researchers, data analysts, and machine learning practitioners.
R 2,381.00
