Matlab 7 Programming Tips下载

weixin_39821260 2023-08-09 09:30:28

分别介绍了帮助文件，编程环境，程序调试，输入输出等不同方面的Matlab使用技巧。英文，共66页，感觉蛮实用的。 , 相关下载链接：https://download.csdn.net/download/creasy_wu/345740?utm_source=bbsseo

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Accelerating MATLAB Performance: 1001 tips to speed up MATLAB programs By 作者: Yair M. Altman ISBN-10 书号: 1482211297 ISBN-13 书号: 9781482211290 Edition 版本: 1 出版日期: 2014-12-11 pages 页数: 785 $105 The MATLAB® programming environment is often perceived as a platform suitable for prototyping and modeling but not for “serious” applications. One of the main complaints is that MATLAB is just too slow. Accelerating MATLAB Performance aims to correct this perception by describing multiple ways to greatly improve MATLAB program speed. Packed with thousands of helpful tips, it leaves no stone unturned, discussing every aspect of MATLAB. Ideal for novices and professionals alike, the book describes MATLAB performance in a scale and depth never before published. It takes a comprehensive approach to MATLAB performance, illustrating numerous ways to attain the desired speedup. The book covers MATLAB, CPU, and memory profiling and discusses various tradeoffs in performance tuning. It describes the application in MATLAB of standard tuning techniques used in the software industry, as well as methods that are specific to MATLAB such as using different data types or built-in functions. The book discusses MATLAB vectorization, parallelization (implicit and explicit), optimization, memory management, chunking, and caching. It explains MATLAB’s memory model and details how it can be leveraged. It describes the use of GPU, MEX, FPGA, and other forms of compiled code, as well as techniques for speeding up deployed applications. It details specific tips for MATLAB GUI, graphics, and I/O. It also reviews a wide variety of utilities, libraries, and toolboxes that can help to improve performance. Sufficient information is provided to allow readers to immediately apply the suggestions to their own MATLAB programs. Extensive references are also included to allow those who wish to expand the treatment of a particular topic to do so easily. Supported by an active website and numerous code examples, the book will help readers rapidly attain significant reductions in development costs and program run times

Accelerating MATLAB Performance - 1001 Tips to Speed Up MATLAB Programs MATLAB 程序加速技巧 http://undocumentedmatlab.com/books/matlab-performance Accelerating MATLAB Performance: 1001 Tips to Speed Up MATLAB Programs by Yair M. Altman English | 2014 | ISBN: 1482211300 | 785 pages | PDF | 145 MB Features Demonstrates how to improve MATLAB® speed in many different ways Shows how to profile MATLAB code to identify performance hotspots Discusses various tradeoffs in MATLAB performance tuning Addresses vectorization, parallelization, distributed computing, caching, optimization, memory management, GUI, graphics, and I/O Explains using GPU, MEX, MATLAB toolboxes and external libraries Contains programming tips useful to novices and professionals alike Includes thousands of tips, code examples, and online references Supported by an active website Summary The MATLAB® programming environment is often perceived as a platform suitable for prototyping and modeling but not for "serious" applications. One of the main complaints is that MATLAB is just too slow. Accelerating MATLAB Performance aims to correct this perception by describing multiple ways to greatly improve MATLAB program speed. Packed with thousands of helpful tips, it leaves no stone unturned, discussing every aspect of MATLAB. Ideal for novices and professionals alike, the book describes MATLAB performance in a scale and depth never before published. It takes a comprehensive approach to MATLAB performance, illustrating numerous ways to attain the desired speedup. The book covers MATLAB, CPU, and memory profiling and discusses various tradeoffs in performance tuning. It describes both the application of standard industry techniques in MATLAB, as well as methods that are specific to MATLAB such as using different data types or built-in functions. The book covers MATLAB vectorization, parallelization (implicit and explicit), optimization, memory management, chunking, and caching. It explains MATLAB’s memory model and details how it can be leveraged. It describes the use of GPU, MEX, FPGA, and other forms of compiled code, as well as techniques for speeding up deployed applications. It details specific tips for MATLAB GUI, graphics, and I/O. It also reviews a wide variety of utilities, libraries, and toolboxes that can help to improve performance. Sufficient information is provided to allow readers to immediately apply the suggestions to their own MATLAB programs. Extensive references are also included to allow those who wish to expand the treatment of a particular topic to do so easily. Supported by an active website, and numerous code examples, the book will help readers rapidly attain significant reductions in development costs and program run times.

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