Real-time Design Patterns

Real-time Design Patterns
Author: Bruce Powel Douglass
Publisher: Addison-Wesley Professional
Total Pages: 528
Release: 2003
Genre: Computers
ISBN: 9780201699562


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This revised and enlarged edition of a classic in Old Testament scholarship reflects the most up-to-date research on the prophetic books and offers substantially expanded discussions of important new insight on Isaiah and the other prophets.


Real-time Design Patterns
Language: en
Pages: 528
Authors: Bruce Powel Douglass
Categories: Computers
Type: BOOK - Published: 2003 - Publisher: Addison-Wesley Professional

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This revised and enlarged edition of a classic in Old Testament scholarship reflects the most up-to-date research on the prophetic books and offers substantiall
Design Patterns for Embedded Systems in C
Language: en
Pages: 471
Authors: Bruce Powel Douglass
Categories: Computers
Type: BOOK - Published: 2010-11-03 - Publisher: Elsevier

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A recent survey stated that 52% of embedded projects are late by 4-5 months. This book can help get those projects in on-time with design patterns. The author c
Real Time UML Workshop for Embedded Systems
Language: en
Pages: 432
Authors: Bruce Powel Douglass
Categories: Technology & Engineering
Type: BOOK - Published: 2011-04-01 - Publisher: Elsevier

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This practical new book provides much-needed, practical, hands-on experience capturing analysis and design in UML. It holds the hands of engineers making the di
Real-Time Software Design for Embedded Systems
Language: en
Pages: 613
Authors: Hassan Gomaa
Categories: Computers
Type: BOOK - Published: 2016-05-26 - Publisher: Cambridge University Press

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Organized as an introduction followed by several self-contained chapters, this tutorial takes the reader from use cases to complete architectures for real-time
Machine Learning Design Patterns
Language: en
Pages: 408
Authors: Valliappa Lakshmanan
Categories: Computers
Type: BOOK - Published: 2020-10-15 - Publisher: O'Reilly Media

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The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog pr