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Learning Core Audio: A Hands-On Guide to Audio Programming for Mac and iOS
Introduction to Programming with Fortran: with coverage of Fortran 90, 95, 2003 and 77
Introduction to Programming with Fortran - with coverage of Fortran 90, 95, 2003 and 77
MATLAB - Modelling, Programming and Simulations
-MATLAB: Modelling, Programming and Simulations- ed. by Emilson Pereira Leite (Repost)
Introduction to Programming with Fortran: with coverage of Fortran 90, 95, 2003 and 77 [Repost]
An Introduction to Programming and Numerical Methods in MATLAB [Repost]
"MATLAB: Modelling, Programming and Simulations" ed. by Emilson Pereira Leite (Repost)
Programming Social Applications: Building Viral Experiences with OpenSocial, OAuth, OpenID, and Distributed Web... (repost)
MATLAB Programming for Engineers (2nd edition) [Repost]
Sriranga Veeraraghavan, "Sams Teach Yourself Shell Programming in 24 Hours" (Repost)
Programming Computer Vision with Python - Tools and algorithms for analyzing images
Matlab: A Practical Introduction to Programming and Problem Solving (2nd edition) [Repost]
ECOOP 2011 - Object-Oriented Programming
Mobile JavaScript Application Development - Bringing Web Programming to Mobile Devices [Paperback]
Concurrent Programming on Windows (repost)
Expert WSS 3.0 and MOSS 2007 Programming (repost)
Embedded Software Design and Programming of Multiprocessor System-on-Chip (repost)
OpenCV 2 Computer Vision Application Programming Cookbook
Programming Computer Vision with Python: Tools and algorithms for analyzing images
Introduction to Programming with Fortran: with coverage of Fortran 90, 95, 2003 and 77
Introduction to Programming with Fortran - with coverage of Fortran 90, 95, 2003 and 77
MATLAB - Modelling, Programming and Simulations
-MATLAB: Modelling, Programming and Simulations- ed. by Emilson Pereira Leite (Repost)
Introduction to Programming with Fortran: with coverage of Fortran 90, 95, 2003 and 77 [Repost]
An Introduction to Programming and Numerical Methods in MATLAB [Repost]
"MATLAB: Modelling, Programming and Simulations" ed. by Emilson Pereira Leite (Repost)
Programming Social Applications: Building Viral Experiences with OpenSocial, OAuth, OpenID, and Distributed Web... (repost)
MATLAB Programming for Engineers (2nd edition) [Repost]
Sriranga Veeraraghavan, "Sams Teach Yourself Shell Programming in 24 Hours" (Repost)
Programming Computer Vision with Python - Tools and algorithms for analyzing images
Matlab: A Practical Introduction to Programming and Problem Solving (2nd edition) [Repost]
ECOOP 2011 - Object-Oriented Programming
Mobile JavaScript Application Development - Bringing Web Programming to Mobile Devices [Paperback]
Concurrent Programming on Windows (repost)
Expert WSS 3.0 and MOSS 2007 Programming (repost)
Embedded Software Design and Programming of Multiprocessor System-on-Chip (repost)
OpenCV 2 Computer Vision Application Programming Cookbook
Programming Computer Vision with Python: Tools and algorithms for analyzing images
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Programming Handbook of Data Structures and Applications
Posted on 2010-03-27
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Although there are many advanced and specialized texts and handbooks on algorithms, until now there was no book that focused exclusively on the wide variety of data structures that have been reported in the literature. The Handbook of Data Structures and Applications responds to the needs of students, professionals, and researchers who need a mainstream reference on data structures by providing a comprehensive survey of data structures of various types. Divided into seven parts, the text begins with a review of introductory material, followed by a discussion of well-known classes of data structures, Priority Queues, Dictionary Structures, and Multidimensional structures. The editors next analyze miscellaneous data structures, which are well-known structures that elude easy classification. The book then addresses mechanisms and tools that were developed to facilitate the use of data structures in real programs. It concludes with an examination of the applications of data structures. The Handbook is invaluable in suggesting new ideas for research in data structures, and for revealing application contexts in which they can be deployed. Practitioners devising algorithms will gain insight into organizing data, allowing them to solve algorithmic problems more efficiently.
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