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Introduction to Mixed-Signal, Embedded Design
by Alex Doboli Edward H. CurrieThis textbook is written for junior/senior undergraduate and first-year graduate students in the electrical and computer engineering departments. Using PSoC mixed-signal array design, the authors define the characteristics of embedd design, embedded mixed-signal architectures, and top-down design. Optimized implementations of these designs are included to illustrate the theory. Exercises are provided at the end of each chapter for practice. Topics covered include the hardware and software used to implement analog and digital interfaces, various filter structures, amplifiers and other signal-conditioning circuits, pulse-width modulators, timers, and data structures for handling multiple similar peripheral devices. The practical exercises contained in the companion laboratory manual, which was co-authored by Cypress Staff Applications Engineer Dave Van Ess, are also based on PSoC. PSoC's integrated microcontroller, highly configurable analog/digital peripherals, and a full set of development tools make it an ideal learning tool for developing mixed-signal embedded design skills.
Introduction to Modeling and Numerical Methods for Biomedical and Chemical Engineers
by Edward GatzkeThis textbook introduces the concepts and tools that biomedical and chemical engineering students need to know in order to translate engineering problems into a numerical representation using scientific fundamentals. Modeling concepts focus on problems that are directly related to biomedical and chemical engineering. A variety of computational tools are presented, including MATLAB, Excel, Mathcad, and COMSOL, and a brief introduction to each tool is accompanied by multiple computer lab experiences. The numerical methods covered are basic linear algebra and basic statistics, and traditional methods like Newton’s method, Euler Integration, and trapezoidal integration. The book presents the reader with numerous examples and worked problems, and practice problems are included at the end of each chapter.
Introduction to Modeling and Simulation with MATLAB® and Python (Chapman & Hall/CRC Computational Science)
by Steven I. Gordon Brian GuilfoosIntroduction to Modeling and Simulation with MATLAB and Python is intended for students and professionals in science, social science, and engineering that wish to learn the principles of computer modeling, as well as basic programming skills. The book content focuses on meeting a set of basic modeling and simulation competencies that were developed as part of several National Science Foundation grants. Even though computer science students are much more expert programmers, they are not often given the opportunity to see how those skills are being applied to solve complex science and engineering problems and may also not be aware of the libraries used by scientists to create those models. The book interleaves chapters on modeling concepts and related exercises with programming concepts and exercises. The authors start with an introduction to modeling and its importance to current practices in the sciences and engineering. They introduce each of the programming environments and the syntax used to represent variables and compute mathematical equations and functions. As students gain more programming expertise, the authors return to modeling concepts, providing starting code for a variety of exercises where students add additional code to solve the problem and provide an analysis of the outcomes. In this way, the book builds both modeling and programming expertise with a "just-in-time" approach so that by the end of the book, students can take on relatively simple modeling example on their own. Each chapter is supplemented with references to additional reading, tutorials, and exercises that guide students to additional help and allows them to practice both their programming and analytical modeling skills. In addition, each of the programming related chapters is divided into two parts – one for MATLAB and one for Python. In these chapters, the authors also refer to additional online tutorials that students can use if they are having difficulty with any of the topics. The book culminates with a set of final project exercise suggestions that incorporate both the modeling and programming skills provided in the rest of the volume. Those projects could be undertaken by individuals or small groups of students. The companion website at http://www.intromodeling.com provides updates to instructions when there are substantial changes in software versions, as well as electronic copies of exercises and the related code. The website also offers a space where people can suggest additional projects they are willing to share as well as comments on the existing projects and exercises throughout the book. Solutions and lecture notes will also be available for qualifying instructors.
Introduction to Modeling Cognitive Processes
by Tom VergutsAn introduction to computational modeling for cognitive neuroscientists, covering both foundational work and recent developments. Cognitive neuroscientists need sophisticated conceptual tools to make sense of their field&’s proliferation of novel theories, methods, and data. Computational modeling is such a tool, enabling researchers to turn theories into precise formulations. This book offers a mathematically gentle and theoretically unified introduction to modeling cognitive processes. Theoretical exercises of varying degrees of difficulty throughout help readers develop their modeling skills. After a general introduction to cognitive modeling and optimization, the book covers models of decision making; supervised learning algorithms, including Hebbian learning, delta rule, and backpropagation; the statistical model analysis methods of model parameter estimation and model evaluation; the three recent cognitive modeling approaches of reinforcement learning, unsupervised learning, and Bayesian models; and models of social interaction. All mathematical concepts are introduced gradually, with no background in advanced topics required. Hints and solutions for exercises and a glossary follow the main text. All code in the book is Python, with the Spyder editor in the Anaconda environment. A GitHub repository with Python files enables readers to access the computer code used and start programming themselves. The book is suitable as an introduction to modeling cognitive processes for students across a range of disciplines and as a reference for researchers interested in a broad overview.
Introduction to Modeling Convection in Planets and Stars: Magnetic Field, Density Stratification, Rotation (Princeton Series in Astrophysics #24)
by Gary A. GlatzmaierThis book provides readers with the skills they need to write computer codes that simulate convection, internal gravity waves, and magnetic field generation in the interiors and atmospheres of rotating planets and stars. Using a teaching method perfected in the classroom, Gary Glatzmaier begins by offering a step-by-step guide on how to design codes for simulating nonlinear time-dependent thermal convection in a two-dimensional box using Fourier expansions in the horizontal direction and finite differences in the vertical direction. He then describes how to implement more efficient and accurate numerical methods and more realistic geometries in two and three dimensions. In the third part of the book, Glatzmaier demonstrates how to incorporate more sophisticated physics, including the effects of magnetic field, density stratification, and rotation. Featuring numerous exercises throughout, this is an ideal textbook for students and an essential resource for researchers. Describes how to create codes that simulate the internal dynamics of planets and stars Builds on basic concepts and simple methods Shows how to improve the efficiency and accuracy of the numerical methods Describes more relevant geometries and boundary conditions Demonstrates how to incorporate more sophisticated physics
Introduction to Modeling for Biosciences
by Dominique Chu David J. BarnesMathematical modeling can be a useful tool for researchers in the biological scientists. Yet in biological modeling there is no one modeling technique that is suitable for all problems. Instead, different problems call for different approaches. Furthermore, it can be helpful to analyze the same system using a variety of approaches, to be able to exploit the advantages and drawbacks of each. In practice, it is often unclear which modeling approaches will be most suitable for a particular biological question, a problem which requires researchers to know a reasonable amount about a number of techniques, rather than become experts on a single one. "Introduction to Modeling for Biosciences" addresses this issue by presenting a broad overview of the most important techniques used to model biological systems. In addition to providing an introduction into the use of a wide range of software tools and modeling environments, this helpful text/reference describes the constraints and difficulties that each modeling technique presents in practice, enabling the researcher to quickly determine which software package would be most useful for their particular problem. Topics and features: introduces a basic array of techniques to formulate models of biological systems, and to solve them; intersperses the text with exercises throughout the book; includes practical introductions to the Maxima computer algebra system, the PRISM model checker, and the Repast Simphony agent modeling environment; discusses agent-based models, stochastic modeling techniques, differential equations and Gillespie's stochastic simulation algorithm; contains appendices on Repast batch running, rules of differentiation and integration, Maxima and PRISM notation, and some additional mathematical concepts; supplies source code for many of the example models discussed, at the associated website http://www.cs.kent.ac.uk/imb/. This unique and practical guide leads the novice modeler through realistic and concrete modeling projects, highlighting and commenting on the process of abstracting the real system into a model. Students and active researchers in the biosciences will also benefit from the discussions of the high-quality, tried-and-tested modeling tools described in the book. Dr. David J. Barnes is a lecturer in computer science at the University of Kent, UK, with a strong background in the teaching of programming. Dr. Dominique Chu is a lecturer in computer science at the University of Kent, UK. He is an internationally recognized expert in agent-based modeling, and has also in-depth research experience in stochastic and differential equation based modeling.
Introduction to Modern Cryptography (Chapman & Hall/CRC Cryptography and Network Security Series)
by Jonathan Katz Yehuda LindellNow the most used texbook for introductory cryptography courses in both mathematics and computer science, the Third Edition builds upon previous editions by offering several new sections, topics, and exercises. The authors present the core principles of modern cryptography, with emphasis on formal definitions, rigorous proofs of security.
Introduction to Modern Digital Holography
by Ting-Chung Poon Jung-Ping LiuGet up to speed with digital holography with this concise and straightforward introduction to modern techniques and conventions. Building up from the basic principles of optics, this book describes key techniques in digital holography, such as phase-shifting holography, low-coherence holography, diffraction tomographic holography and optical scanning holography, discussing their practical applications, and accompanied by all the theory necessary to understand the underlying principles at work. A further chapter covers advanced techniques for producing computer-generated holograms. Extensive Matlab code is integrated with the text throughout and available for download online, illustrating both theoretical results and practical considerations such as aliasing, zero padding and sampling. Accompanied by end-of-chapter problems and an online solutions manual for instructors, this is an indispensable resource for students, researchers and engineers in the fields of optical image processing and digital holography.
Introduction to Modern Sleep Technology
by Shih-Chun Kang Rayleigh Ping-Ying ChiangSleep medicine has been developing for more than 40 years. The current concepts in sleep technology are mainly centered on polysomnography (PSG) and issues related to sleep technicians. However, the editors believe that the true value of technology is revealed only when benefits to humanity are manifest. To this end, they endeavor to create a new era in sleep technology, one that will improve the quality of people's sleep and daily lives.This edited book, Introduction to Modern Sleep Technology, provides a comprehensive reference volume to the latest advancements in the area of Sleep Technology. It offers an excellent range of insights and opinions from leading researchers and experts in multiple disciplines spanning academia, clinical practice and industry. Up-to-date insights into the current research topics in this field are featured in addition to the latest technological advances with reference to appropriate working examples.The current book combines the five dimensions of knowledge, i.e., sleep medicine, clinical psychology engineering, industrial design and technology management to ensure the content is applicable to people's daily lives. This edited book, Introduction to Modern Sleep Technology, provides a comprehensive reference volume to the latest advancements in the area of Sleep Technology. It offers an excellent range of insights and opinions from leading researchers and experts in multiple disciplines spanning academia, clinical practice and industry. Up-to-date insights into the current research topics in this field are featured in addition to the latest technological advances with reference to appropriate working examples.The current book combines the five dimensions of knowledge, i.e., sleep medicine, clinical psychology engineering, industrial design and technology management to ensure the content is applicable to people's daily lives. The current book combines the five dimensions of knowledge, i.e., sleep medicine, clinical psychology engineering, industrial design and technology management to ensure the content is applicable to people's daily lives.
An Introduction to Modern Timekeeping and Time Transfer (Springer Series in Measurement Science and Technology)
by Parameswar Banerjee Demetrios MatsakisThis book provides a comprehensive, systematic description of modern timekeeping and its specializations. Introductory chapters discuss the concept of time and its definition, then briefly look at pre-Atomic Era timekeeping to set the stage for the introduction of the atomic clock. Subsequent chapters focus on concepts such as frequency stability and measurement uncertainty, as well as computer network time-synchronization protocols including Network Time Protocol (NTP) and Precise Time Protocol (PTP). The book then delves into the nuts and bolts of the Global Navigation Satellite Systems (GNSS), Two-Way Satellite Time and Frequency Transfer, and Optical Time and Frequency Transfer. Timescale theory is then described as a way to combine clock data, and the algorithms and procedures used to generate Coordinated Universal Time (UTC) are given. Finally, there is a look at modern applications of timekeeping and time transfer.Featuring a glossary of all key terms, this book is highly recommended for trained or incoming physicists, engineers, or mathematicians working, for example, in manufacturing or timing laboratories. Additionally, it is suitable for use in introductory university courses dealing with the subject of timekeeping.
Introduction to MongoDB, Express, Angular and Node.js
by Paul OluyegeThis book is ideal for beginners and intermediate front-end developers who want to become a full-stack JavaScript developers and are looking forward to quickly work through an intelligent example that demonstrates all the key features of full-stack development using MEAN technologies. You'll need some prior exposure to MongoDB as we skim over its basics and get straight to work.
Introduction to Natural Language Processing (Adaptive Computation and Machine Learning series)
by Jacob EisensteinA survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques.This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation.The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.
An Introduction to Network Programming with Java: Java 7 Compatible
by Jan GrabaSince the second edition of this text, the use of the Internet and networks generally has continued to expand at a phenomenal rate. This has led to both an increase in demand for network software and to improvements in the technology used to run such networks, with the latter naturally leading to changes in the former. During this time, the Java libraries have been updated to keep up with the new developments in network technology, so that the Java programming language continues to be one of the mainstays of network software development. In providing a very readable text that avoids getting immersed in low-level technical details, while still providing a useful, practical guide to network programming for both undergraduates and busy IT professionals, this third edition continues the trend of its predecessors. To retain its currency, the text has been updated to reflect changes that have taken place in Java's network technology over the past seven years (including the release of Java 7), whilst retaining its notable features of numerous code examples, screenshots and end-of-chapter exercises.
Introduction to Network Security: Theory and Practice
by Jie Wang Zachary A. KisselIntroductory textbook in the important area of network security for undergraduate and graduate students Comprehensively covers fundamental concepts with newer topics such as electronic cash, bit-coin, P2P, SHA-3, E-voting, and Zigbee security Fully updated to reflect new developments in network security Introduces a chapter on Cloud security, a very popular and essential topic Uses everyday examples that most computer users experience to illustrate important principles and mechanisms Features a companion website with Powerpoint slides for lectures and solution manuals to selected exercise problems, available at http://www.cs.uml.edu/~wang/NetSec
Introduction to Networking
by Wendell OdomIntroduction to Networking provides you with a comprehensive overview of the technologies and standards that make the modern connected world a reality. Requiring no previous knowledge of computer networking, this textbook takes you on a tour of the building blocks of modern-day networks. Major concepts, such as OSI and TCP/IP models, network media specifications and functions, LAN/WAN protocols, topologies, and capabilities, are covered in detail. Industry standards and a brief historical development of major networking technologies are surveyed in conjunction with basic awareness of software and hardware components used in typical networking and internetworking environments. <p><p>Expert instructor and best-selling author Wendell Odom provides you with a solid foundation of how computer networks function. He then shows you how to build both local-area networks (LAN) and wide-area networks (WAN) for transmission of data over short and long distances. You also learn how TCP/IP uses these LANs and WANs to create corporate networks and the worldwide Internet. The book concludes by showing you how networking connects applications you use on a daily basis with resources that reside on the global Internet. <p><p>Full of real-world practical examples, Introduction to Networking provides you with the foundation knowledge and skills you need to start a career in networking.
Introduction To Networking With Network+
by Microsoft Official Academic Course Staff Timothy PintelloIntroduction to Networking with Network + is the cornerstone for your networking curriculum. It is built around the new Network+ 2012 framework. It is based upon the CompTIA Network+ certification and covers the most recent exam objectives. Are you tired of books that cover new technologies and exam topics in a fleeting fashion, and are bogged down with legacy technology coverage that is now out-dated? This book by Timothy Pintello is up-to-date and covers only relevant and current technologies. This book also includes his revolutionary method for making Subnetting easily understood by new IT
Introduction to Networks: Lab Manual, v5.0
by Cisco Networking Academy Program StaffThe Introduction to Networks Lab Manual provides students enrolled in a Cisco Networking Academy Introduction to Networks course with a convenient, complete collection of all the course lab exercises that provide hands-on practice and challenges.
Introduction to Networks Companion Guide [Cisco Networking Academy Series]
by Cisco Networking AcademyIntroduction to Networks Companion Guide is the official supplemental textbook for the Introduction to Networks course in the Cisco® Networking Academy® CCNA® Routing and Switching curriculum. The course introduces the architecture, structure, functions, components, and models of the Internet and computer networks.
Introduction to Networks Course Booklet (CCNA)
by Cisco Networking AcademyYour Cisco Networking Academy® Course Booklet is designed as a study resource you can easily read, highlight, and review on the go, wherever the Internet is not available or practical: The text is extracted directly, word-for-word, from the online course so you can highlight important points and take notes in the “Your Chapter Notes” section. Headings with the exact page correlations provide a quick reference to the online course for your classroom discussions and exam preparation. An icon system directs you to the online curriculum to take full advantage of the images embedded within the Networking Academy online course interface and reminds you to do the labs, interactive activities, packet tracer activities, watch videos, and take the chapter quizzes. <p><p> The Course Booklet is a basic, economical paper-based resource to help you succeed with the Cisco Networking Academy online course. <p><p> This book is offered exclusively for students enrolled in Cisco Networking Academy courses. It is not designed for independent study or professional certification preparation. Visit netacad.com to learn more about program options and requirements.
Introduction to Networks Lab Manual, Version 5.1
by Cisco Networking AcademyThis manual provides students enrolled in a Cisco Networking Academy Introduction to Networks course with a convenient, complete collection of all the course lab exercises that provide hands-on practice and challenges.
An Introduction to Neural Information Processing
by Fanji Gu Peiji Liang Si WuThis book provides an overview of neural information processing research, which is one of the most important branches of neuroscience today. Neural information processing is an interdisciplinary subject, and the merging interaction between neuroscience and mathematics, physics, as well as information science plays a key role in the development of this field. This book begins with the anatomy of the central nervous system, followed by an introduction to various information processing models at different levels. The authors all have extensive experience in mathematics, physics and biomedical engineering, and have worked in this multidisciplinary area for a number of years. They present classical examples of how the pioneers in this field used theoretical analysis, mathematical modeling and computer simulation to solve neurobiological problems, and share their experiences and lessons learned. The book is intended for researchers and students with a mathematics, physics or informatics background who are interested in brain research and keen to understand the necessary neurobiology and how they can use their specialties to address neurobiological problems. It is also provides inspiration for neuroscience students who are interested in learning how to use mathematics, physics or informatics approaches to solve problems in their field.
An Introduction to Neural Network Methods for Differential Equations (SpringerBriefs in Applied Sciences and Technology)
by Manoj Kumar Neha Yadav Anupam YadavThis book introduces a variety of neural network methods for solving differential equations arising in science and engineering. The emphasis is placed on a deep understanding of the neural network techniques, which has been presented in a mostly heuristic and intuitive manner. This approach will enable the reader to understand the working, efficiency and shortcomings of each neural network technique for solving differential equations. The objective of this book is to provide the reader with a sound understanding of the foundations of neural networks and a comprehensive introduction to neural network methods for solving differential equations together with recent developments in the techniques and their applications. The book comprises four major sections. Section I consists of a brief overview of differential equations and the relevant physical problems arising in science and engineering. Section II illustrates the history of neural networks starting from their beginnings in the 1940s through to the renewed interest of the 1980s. A general introduction to neural networks and learning technologies is presented in Section III. This section also includes the description of the multilayer perceptron and its learning methods. In Section IV, the different neural network methods for solving differential equations are introduced, including discussion of the most recent developments in the field. Advanced students and researchers in mathematics, computer science and various disciplines in science and engineering will find this book a valuable reference source.
Introduction to Non-Invasive EEG-Based Brain-Computer Interfaces for Assistive Technologies
by Teodiano Freire Bastos-FilhoThis book aims to bring to the reader an overview of different applications of brain-computer interfaces (BCIs) based on more than 20 years of experience working on these interfaces. The author provides a review of the human brain and EEG signals, describing the human brain, anatomically and physiologically, with the objective of showing some of the patterns of EEG (electroencephalogram) signals used to control BCIs. It then introduces BCIs and different applications, such as a BCI based on ERD/ERS Patterns in α rhythms (used to command a robotic wheelchair with an augmentative and alternative communication (AAC) system onboard it); a BCI based on dependent-SSVEP to command the same robotic wheelchair; a BCI based on SSVEP to command a telepresence robot and its onboard AAC system; a BCI based on SSVEP to command an autonomous car; a BCI based on independent-SSVEP (using Depth-of-Field) to command the same robotic wheelchair; the use of compressive technique in SSVEP-based BCI; a BCI based on motor imagery (using different techniques) to command a robotic monocycle and a robotic exoskeleton; and the first steps to build a neurorehabilitation system based on motor imagery of pedalling together an in immersive virtual environment. This book is intended for researchers, professionals and students working on assistive technology.
An Introduction to Number Theory with Cryptography (Textbooks in Mathematics)
by James Kraft Lawrence Washington<p>Building on the success of the first edition, An Introduction to Number Theory with Cryptography, Second Edition, increases coverage of the popular and important topic of cryptography, integrating it with traditional topics in number theory. <p>The authors have written the text in an engaging style to reflect number theory's increasing popularity. The book is designed to be used by sophomore, junior, and senior undergraduates, but it is also accessible to advanced high school students and is appropriate for independent study. It includes a few more advanced topics for students who wish to explore beyond the traditional curriculum.</p>
An Introduction to Object Recognition: Selected Algorithms for a Wide Variety of Applications (Advances in Computer Vision and Pattern Recognition)
by Marco Alexander TreiberRapid development of computer hardware has enabled usage of automatic object recognition in an increasing number of applications, ranging from industrial image processing to medical applications, as well as tasks triggered by the widespread use of the internet. Each area of application has its specific requirements, and consequently these cannot all be tackled appropriately by a single, general-purpose algorithm. This easy-to-read text/reference provides a comprehensive introduction to the field of object recognition (OR). The book presents an overview of the diverse applications for OR and highlights important algorithm classes, presenting representative example algorithms for each class. The presentation of each algorithm describes the basic algorithm flow in detail, complete with graphical illustrations. Pseudocode implementations are also included for many of the methods, and definitions are supplied for terms which may be unfamiliar to the novice reader. Supporting a clear and intuitive tutorial style, the usage of mathematics is kept to a minimum. Topics and features: presents example algorithms covering global approaches, transformation-search-based methods, geometrical model driven methods, 3D object recognition schemes, flexible contour fitting algorithms, and descriptor-based methods; explores each method in its entirety, rather than focusing on individual steps in isolation, with a detailed description of the flow of each algorithm, including graphical illustrations; explains the important concepts at length in a simple-to-understand style, with a minimum usage of mathematics; discusses a broad spectrum of applications, including some examples from commercial products; contains appendices discussing topics related to OR and widely used in the algorithms, (but not at the core of the methods described in the chapters). Practitioners of industrial image processing will find this simple introduction and overview to OR a valuable reference, as will graduate students in computer vision courses. Marco Treiber is a software developer at Siemens Electronics Assembly Systems, Munich, Germany, where he is Technical Lead in Image Processing for the Vision System of SiPlace placement machines, used in SMT assembly.