包括使用修正Gram-Schmit算法實現QR分解，自編LU分解、利用冪法和反冪法計算矩陣最大和最小特征值的程序。例外附有使用這些算法的例子供參考。 QR decomposition algorithm based on modified Gram-Schmit LU decomposition algorithm algorithm used to find maximum and minimum eigenvalue based on power and inverse power method and some EXAMPLES are also included.
一種比較好的抗鋸齒算法
Add myaa.m to your path and enjoy anti-aliased professionally looking graphics in Matlab at any time. Myaa works with any kind of graphic (3-D, plots, scatterplots, ...) and even adds anti-aliasing to text, ui controls and grids. Myaa is ideal for complex, cluttered and saturated plots.
See attached screenshot for a demonstration. More EXAMPLES included in the code, just run help myaa .
Curiosa:
For those of you who publish your code often, an undocumented anti-aliasing option is included in the snapnow.m function in Matlab. To publish a file called test.m you can do:
opts.figureSnapMethod = antialiased
publish( test.m ,opts)
However, you will have more control over the process using myaa, which is also the best choice when using Matlab interactively.
一個J2EE四層架構的實例，采用jsp+javabean+sessionbean+entitybean做的,與大家共享： 1.開發環境用的jbuilder7.0+weblogic7.0+oracle9i(sqlserver2000) 2.sql語句如下： create table ejbAccounts (id varchar(15), bal float, type varchar(15)) 3.現在weblogic console下建立好數據源名：EXAMPLES-dataSource-mssqlserverXAPool 4.可以用客戶端測試和網頁測試.
用20個示例項目的方式介紹Matlab/Simulink。內容包括：
*Contains over 20 hands-on projects in MATLAB(with code) integrated throughout the book *Includes a complete introduction to Simulink *Accompanied by a CD-ROM containing MATLAB EXAMPLES, source code, third party simulations & projects *Suitable for self-study and professional licensing exams *Designed for the reader who does not have extensive math and programming experience *Contains many practical applications of MATLAB and Simulink
Recent advances in experimental methods have resulted in the generation
of enormous volumes of data across the life sciences. Hence clustering and
classification techniques that were once predominantly the domain of ecologists
are now being used more widely. This book provides an overview of these
important data analysis methods, from long-established statistical methods
to more recent machine learning techniques. It aims to provide a framework
that will enable the reader to recognise the assumptions and constraints that
are implicit in all such techniques. Important generic issues are discussed first
and then the major families of algorithms are described. Throughout the focus
is on explanation and understanding and readers are directed to other resources
that provide additional mathematical rigour when it is required. EXAMPLES
taken from across the whole of biology, including bioinformatics, are provided
throughout the book to illustrate the key concepts and each technique’s
potential.
Jvm 規范說明。The Java Virtual Machine was designed to support the Java programming language. Some concepts and vocabulary from the Java language are thus necessary to understand the virtual machine. This chapter gives enough of an overview of Java to support the discussion of the Java Virtual Machine to follow. Its material has been condensed from The Java Language Specification, by James Gosling, Bill Joy, and Guy Steele. For a complete discussion of the Java language, or for details and EXAMPLES of the material in this chapter, refer to that book. Readers familiar with that book may wish to skip this chapter. Readers familiar with Java, but not with The Java Language Specification, should at least skim this chapter for the terminology it introduces.
jsp和xml。XML and JSP are two important tools available in producing a web application. This chapter examines the
potential of mixing these two technologies in order to enhance the capabilities of JSP. While this chapter will
cover many things about XML, this chapter will not attempt to teach XML. Instead it focuses on how JSP and
XML can be used together as a highly flexible and powerful tool. In general the usage of XML in these
EXAMPLES will be kept simple and should cause no problems for users who are starting XML.
