Quantum Computing for Programmers and Investors


Book Description

This book is aimed at people who simply know the basics of computer programming. It does not require any notion of physics and allows its readers to understand with total accuracy and in the simplest way the use that could be made of a quantum computer, by explaining step by step how to write a software to emulate its operation. The usual expression that a qubit “is an object that can be simultaneously in both binary states 0 and 1” will lose all the aura of mystery that surrounds it, and readers will understand exactly its meaning and implications for computing without the need for any knowledge of physics. The book describes quantum computing by considering it strictly from a computer science point of view, simply as a machine that is capable of transforming a given input into a given output using any suitable physical principle to work, and thus allows to become completely familiar with quantum gates and with the most famous quantum algorithms. The only condition is that the readers are familiar with some programming language and with the basic concepts of classical computer science: those who have this knowledge will easily follow the description of quantum algorithms and understand the software emulation that is implemented in the book, and will also have fun running and testing it with their own PC. The knowledge acquired through this book is of vital importance to investors because it allows them to judge independently on the risk of investing in this technology. It has been written for programmers because the knowledge of basics of computer science is useful to understand exactly what a quantum computer, once built, could be used for. But this understanding is also essential for investors who must evaluate whether and how much it is appropriate to risk investing in the development of quantum computing. Therefore, even investors (private investors, consultants, managers of financing funds for technological enterprises, etc.) who want to decide on the allocation of resources in quantum computing with full knowledge of the stakes, must know this book, and if they do not personally own the necessary prerequisites, they can use it by hiring some trusted computer expert to read it, understand it and report on the result.




Water Spectrum


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Modern Algorithms for Image Processing


Book Description

Utilize modern methods for digital image processing and take advantage of the many time-saving templates provided for all of the projects in this book. Modern Algorithms for Image Processing approaches the topic of image processing through teaching by example. Throughout the book, you will create projects that resolve typical problems that you might encounter in the world of digital image processing. Some projects teach you methods for addressing the quality of images, such as reducing random errors or noise and suppressing pulse noise (salt and pepper), a method valuable for improving the quality of historical images. Other methods detail how to correct inhomogeneous illumination, not by means of subtracting the mean illumination, but through division, a far more efficient method. Additional projects cover contrasting, and a process for edge detection, more efficient than Canny's, for detecting edges in color images directly, without converting them into black and white images. What You'll Learn Apply innovative methods for suppressing pulse noise, enhancing contrast, and edge detectionKnow the pros and cons of enlisting a particular method Use new approaches for image compression and recognizing circles in photos Utilize a valuable method for straightening photos of paintings taken at an oblique angle, a critical concept to understand when using flash at a right angle Understand the problem statement of polygonal approximation of boundaries or edges and its solution Use a new method for detecting bicycles in trafficAccess complete source code examples in C# for all of the projects Who This Book Is For C# developers who work with digital image processing or are interested in informatics. The reader should have programming experience and access to an integrated development environment (IDE), ideally .NET. This book does not prove or disprove theorems, but suggests methods for learning valuable concepts that will enable you to customize your own image processing projects.







Toledo City Journal


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C++ Toolbox for Verified Computing I


Book Description

Our aim in writing this book was to provide an extensive set of C++ programs for solving basic numerical problems with verification of the results. This C++ Toolbox for Verified Computing I is the C++ edition of the Numerical Toolbox for Verified Computing l. The programs of the original edition were written in PASCAL-XSC, a PASCAL eXtension for Scientific Computation. Since we published the first edition we have received many requests from readers and users of our tools for a version in C++. We take the view that C++ is growing in importance in the field of numeri cal computing. C++ includes C, but as a typed language and due to its modern concepts, it is superior to C. To obtain the degree of efficiency that PASCAL-XSC provides, we used the C-XSC library. C-XSC is a C++ class library for eXtended Scientific Computing. C++ and the C-XSC library are an adequate alternative to special XSC-Ianguages such as PASCAL-XSC or ACRITH-XSC. A shareware version of the C-XSC library and the sources of the toolbox programs are freely available via anonymous ftp or can be ordered against reimbursement of expenses. The programs of this book do not require a great deal of insight into the features of C++. Particularly, object oriented programming techniques are not required.




The R Book


Book Description

Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research. This edition: Features full colour text and extensive graphics throughout. Introduces a clear structure with numbered section headings to help readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis and Meta-Analysis. Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user. Praise for the first edition: ‘...if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.’ (The American Statistician, August 2008) ‘The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book...’ (Professional Pensions, July 2007)




U.S.D.A. Forest Service Research Note RM.


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