53,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in 1-2 Wochen
payback
27 °P sammeln
  • Gebundenes Buch

This textbook details the variety of number formats used by computers, thereby helping to ground readers in what can and cannot be represented accurately, especially by floating-point numbers.
The book's first part details standard representations of integers and floating-point numbers. The second explores other number representations, including the wide variety recently developed to support artificial intelligence (AI) and its demand for efficiency in representation to accommodate the ever-expanding scope of neural network models. Chapters describe each format, with examples in code…mehr

Produktbeschreibung
This textbook details the variety of number formats used by computers, thereby helping to ground readers in what can and cannot be represented accurately, especially by floating-point numbers.

The book's first part details standard representations of integers and floating-point numbers. The second explores other number representations, including the wide variety recently developed to support artificial intelligence (AI) and its demand for efficiency in representation to accommodate the ever-expanding scope of neural network models. Chapters describe each format, with examples in code (Python and C) and exercises. This new edition includes three new chapters on posits, AI number formats, and a collaborative experiment with an AI to generate novel number formats.

Topics and features:
Explores how computers use numbers to complete operationsAdds new chapters on posits and AI number formatsIncludes exercises and examples that are code snippets in C or PythonImplements and tests new AI-designed number formats (as designed by GPT-4)Provides thorough grounding on what can and cannot be represented accurately
A textbook eminently suitable for undergraduates in computer science, the work also will appeal to software developers, engineers, scientists, AI experts, and anyone who programs for fun.

Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Autorenporträt
Dr. Ronald T. Kneusel is a Senior Data Scientist with L3Harris. He received his Ph.D. in Computer Science from the University of Colorado, Boulder, in machine learning, and his M.S. in Physics from Michigan State University. His background includes work in breast cancer research and early functional MRI (Medical College of Wisconsin) through medical device development (MR, CT, US) to medical imaging and remote sensing image analysis. He has been deeply involved with software development at all levels since his first forays with an 8-bit Apple II+ computer in the early 1980s hooked him for life. Dr. Kneusel is currently working with L3Harris on the application of modern machine learning techniques to remote sensing imagery and related modalities. He is the author of multiple books and peer-reviewed research articles.  
Rezensionen
"This book can be profitably read by anyone who is interested in computers and is willing to occasionally slog through perhaps unfamiliar territory with minimal guidance. ... details are explained thoroughly, with utmost clarity and specificity. Each chapter ends with a summary, recommendations, exercises, and a set of carefully selected references. This small book provides a solid foundation for further exploration and study. It can be especially valuable to computer science and electrical engineering students." (Edgar R. Chavez, Computing Reviews, February, 2016)

"This book is, on one level, a discussion of how computers work with numbers. It tells how computers represent numbers such as integers, floating point numbers, big integers, decimals, and what is more, how one can write one's own routines to operate on numbers. ... If thismakes you wonder about the utility of computers and how to better understand numerical representations and calculations, you will do wellto add this book to your winter reading list." (David S. Mazel, MAA Reviews, maa.org, January, 2016)

"The book starts with an overview on number systems. ... The book is a good source of information for all who wants to learn how numbers are represented in computers and how computations are performed." (Michael Jung, zbMATH 1330.65002, 2016)
"This book ... should be on the bookshelf of every software developer. ... Each chapter has a nicely composed set of exercises and a well-constructed set of references. The book contains numerous algorithmic examples presented throughout the text in C-like code that is easy to follow, as well as a well-organized index. ... Summing Up: Recommended. Upper-division undergraduates, graduate students, researchers/faculty, two-year technical program students, and professionals/practitioners." (J. Beidler, Choice, Vol.53 (4), December, 2015)…mehr