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Algebraic Shift Register Sequences
Pseudo-random sequences are essential ingredients of every modern digital communication system including cellular telephones, GPS, secure internet transactions and satellite imagery. Each application requires pseudo-random sequences with specific statistical properties. This book describes the design, mathematical analysis and implementation of pseudo-random sequences, particularly those generated by shift registers and related architectures such as feedback-with-carry shift registers. The earlier chapters may be used as a textbook in an advanced undergraduate mathematics course or a graduate electrical engineering course; the more advanced chapters provide a reference work for researchers in the field. Background material from algebra, beginning with elementary group theory, is provided in an appendix.
eBook
Case study research in software engineering
Based on their own experiences of in-depth case studies of software projects in international corporations, in this book the authors present detailed practical guidelines on the preparation, conduct, design and reporting of case studies of software engineering. This is the first software engineering specific book on the case study research method.
eBook
3D graphics for game programming
\"Many of computer graphics classes in colleges are focused on real-time rendering and animation. However, it is not easy to nd an appropriate textbook, which presents the state of the art in interactive graphics, is balanced between theory and practicality, and is of a proper length to be covered in a semester. This book is written for answering the need and presents the must-know in interactive graphics. This book ts the advanced undergraduate or beginning graduate classes for 'Computer Graphics' and 'Game Programming.' Another primary reader group of this book may be composed of game developers, who have experience in graphics APIs and shader programming but have felt lack of theoretical background in 3D graphics. A lot of programming manual-like books can be found in the bookstore, but they do not provide a sufficient level of mathematical background for the game developers. Assuming that the readers have minimal understanding of vectors and matrices, this book provides an opportunity to combine their experiences with the background theory of computer graphics\"-- Provided by publisher.
Book
Stochastic Geometry for Wireless Networks
Covering point process theory, random geometric graphs and coverage processes, this rigorous introduction to stochastic geometry will enable you to obtain powerful, general estimates and bounds of wireless network performance and make good design choices for future wireless architectures and protocols that efficiently manage interference effects. Practical engineering applications are integrated with mathematical theory, with an understanding of probability the only prerequisite. At the same time, stochastic geometry is connected to percolation theory and the theory of random geometric graphs and accompanied by a brief introduction to the R statistical computing language. Combining theory and hands-on analytical techniques with practical examples and exercises, this is a comprehensive guide to the spatial stochastic models essential for modelling and analysis of wireless network performance.
eBook
Design for Embedded Image Processing on FPGAs
Dr Donald Bailey starts with introductory material considering the problem of embedded image processing, and how some of the issues may be solved using parallel hardware solutions. Field programmable gate arrays (FPGAs) are introduced as a technology that provides flexible, fine-grained hardware that can readily exploit parallelism within many image processing algorithms. A brief review of FPGA programming languages provides the link between a software mindset normally associated with image processing algorithms, and the hardware mindset required for efficient utilization of a parallel hardware design. The design process for implementing an image processing algorithm on an FPGA is compared with that for a conventional software implementation, with the key differences highlighted. Particular attention is given to the techniques for mapping an algorithm onto an FPGA implementation, considering timing, memory bandwidth and resource constraints, and efficient hardware computational techniques. Extensive coverage is given of a range of low and intermediate level image processing operations, discussing efficient implementations and how these may vary according to the application. The techniques are illustrated with several example applications or case studies from projects or applications the author has been involved with. Issues such as interfacing between the FPGA and peripheral devices are covered briefly, as is designing the system in such a way that it can be more readily debugged and tuned. <ul type=\"disc\"> <li>Provides a bridge between algorithms and hardware</li> <li>Demonstrates how to avoid many of the potential pitfalls</li> <li>Offers practical recommendations and solutions</li> <li>Illustrates several real-world applications and case studies</li> <li>Allows those with software backgrounds to understand efficient hardware implementation</li> </ul> <p><i>Design for Embedded Image Processing on FPGAs</i> is ideal for researchers and engineers in the vision or image processing industry, who are looking at smart sensors, machine vision, and robotic vision, as well as FPGA developers and application engineers.</p> <p>The book can also be used by graduate students studying imaging systems, computer engineering, digital design, circuit design, or computer science. It can also be used as supplementary text for courses in advanced digital design, algorithm and hardware implementation, and digital signal processing and applications.</p> <p>Lecture slides for instructors available at:</p> <p>www.wiley.com/go/bailey/fpga</p>
eBook
Mobile electronic commerce : foundations, development, and applications
\"Mobile commerce transactions continue to soar, driven largely by the ever-increasing adoption and use of smartphones and tablets. The use of this technology gives consumers the flexibility to shop whenever and wherever they want. This book addresses the role of industry, academia, scientists, engineers, professionals, and students in developing innovative new mobile commerce technologies and systems to further improve the consumer experience. It also discusses the impact of mobile commerce on society, economics, culture, organizations, government, industry, and our daily lives. This book brings together experts from multiple disciplines in industry and academia to stimulate new thinking in the development and application of mobile commerce technology. The book covers important mobile commerce topics, such as critical infrastructure management, mobile security issues, new applications and services, emerging development architectures, mobile business solutions, and future research opportunities. In addition to its multidisciplinary approach, the book also provides a cross-cultural approach intended to overcome cultural barriers and accelerate mobile commerce advancement in the global economy. Authors and researchers from around the world discuss a broad spectrum of methods, tools, and guidelines for designing mobile commerce systems and services in different cultures\"-- Provided by publisher.
Book
Causal Inference and Discovery in Python
Demystify causal inference and casual discovery by uncovering causal principles and merging them with powerful machine learning algorithms for observational and experimental data Purchase of the print or Kindle book includes a free PDF eBook
Key Features
Examine Pearlian causal concepts such as structural causal models, interventions, counterfactuals, and moreDiscover modern causal inference techniques for average and heterogenous treatment effect estimationExplore and leverage traditional and modern causal discovery methods
Book Description
Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that elude a purely statistical mindset. Causal Inference and Discovery in Python helps you unlock the potential of causality. You’ll start with basic motivations behind causal thinking and a comprehensive introduction to Pearlian causal concepts, such as structural causal models, interventions, counterfactuals, and more. Each concept is accompanied by a theoretical explanation and a set of practical exercises with Python code. Next, you’ll dive into the world of causal effect estimation, consistently progressing towards modern machine learning methods. Step-by-step, you’ll discover Python causal ecosystem and harness the power of cutting-edge algorithms. You’ll further explore the mechanics of how “causes leave traces” and compare the main families of causal discovery algorithms. The final chapter gives you a broad outlook into the future of causal AI where we examine challenges and opportunities and provide you with a comprehensive list of resources to learn more.
What you will learn
Master the fundamental concepts of causal inferenceDecipher the mysteries of structural causal modelsUnleash the power of the 4-step causal inference process in PythonExplore advanced uplift modeling techniquesUnlock the secrets of modern causal discovery using PythonUse causal inference for social impact and community benefit
Who this book is for
This book is for machine learning engineers, data scientists, and machine learning researchers looking to extend their data science toolkit and explore causal machine learning. It will also help developers familiar with causality who have worked in another technology and want to switch to Python, and data scientists with a history of working with traditional causality who want to learn causal machine learning. It’s also a must-read for tech-savvy entrepreneurs looking to build a competitive edge for their products and go beyond the limitations of traditional machine learning.
eBook