Kalman

本书第一章系统讲述 MATLAB6.5 的集成工作平台，引导读者初会MATLAB 基本用法。 第二、三章系统叙述MATLAB6.1 的四大基本数据类型（数值数组、字符串数组、元胞数组、构架数组），至于其它扩展数据类型（函数句柄、符号数据、内联函数、unit 数组、稀疏类）则另辟章节专述。此后，本书用九个独立章分述MATLAB6.5 的数值计算、符号计算、函数和数据可视、面向对象编程、GUI 交互操作界面设计、EXE 独立应用程序生成、实现不同软件平台交互的API、M-book 数据图形文字环境集成等八大通用功能。本书用专门的一章深入浅出地阐明SIMULINK 的分层建模、仿真功能、与MATLAB 交互的功能。(This book chapter describes the system integration work MATLAB6.5 platform to guide the reader will be the beginning of the basic usage of MATLAB. Second, the system described in Chapter Four MATLAB6.1 basic data types (numeric arrays, string arrays, cell arrays, structure arrays), while the other extended data types (function handle, symbol data, inline functions, unit array , sparse class) then open another chapter specifically stated. Since then, the book chapters are described by nine independent MATLAB6.5 the numerical computation, symbolic computation, functions, and data visualization, object-oriented programming, GUI interactive interface design, EXE standalone application generation software platform to achieve interaction of different API, M-book data in graphical environment for integration of the eight general-purpose language features. This book devoted a chapter in layman s language to clarify the hierarchical SIMULINK modeling, simulation capabilities, and the MATLAB int)

lms算法 用于实现matlab仿真lms算法的程序(lms fliter)

scaling, transfering and rotating the cube

说明：  该代码利用复化辛普深公式求给定函数的数值积分，已知该函数的等分区间。(The code deep with Combined Formula Simpson numerical integration of a given function, the function of the decile range is known.)

initiation to matlab in french langage

用C语言在matlab中实现移位寄存器的程序编写，并实现其功能，效果还可以，大家可以看看。(shift register)

Matlab Models for PHY Design

LTE接收端 ZF 算法的 在 4天线条件下的求解算法----分块求逆，LDLH分解求逆(LTE ZF LDLH )

matlab程序画图，常见分形图，function cantor(A,B) c=1 p=0 figure hold on plot([A(2) B(2)],[A(1) B(1)], r* ) while norm(A(1,:)-B(1,:))>=1 C=[] D=[] for i=1:size(A,1) a=A(i,:)+(B(i,:)-A(i,:))/3 b=A(i,:)+2*(B(i,:)-A(i,:))/3 C=[C A(i,:) b] D=[D a B(i,:)] end A=C B=D p=p+1 (matlab program drawing, common fractal images function cantor(A,B) c=1 p=0 figure hold on plot([A(2) B(2)],[A(1) B(1)], r* ) while norm(A(1,:)-B(1,:))>=1 C=[] D=[] for i=1:size(A,1) a=A(i,:)+(B(i,:)-A(i,:))/3 b=A(i,:)+2*(B(i,:)-A(i,:))/3 C=[C A(i,:) b] D=[D a B(i,:)] end A=C B=D p=p+1 )

Sparse in frequency Compressive Sensing