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Construction of cubic basis spline

各种系统辨识方法，对一阶，二阶，三阶自衡系统进行辨识。用到的方法有面积法等等……(Various system identification method, first, second, third from the value system identification. The methods used in an area of law, etc ... ...)

由于传感器自身以及通信延迟等原因, 使得异步多传感器数据融合问题比同步问题的研究更 切合实际。 对连续时间系统在融合中心和各传感器节点分别进行异步离散化处理,离散后过程噪声与测 量噪声以及测量噪声之间相关,虽然相应连续时间系统中的噪声是不相关的。 最后推导了相关噪声情况 下的异步融合算法,仿真结果说明了算法的有效性。(Due to t he r easons of senso rs in it self and the communication delays, the r esearch of t he asy nchr onous multisensor da ta fusion pr oblem is mo re pr actical than t hat o f synchro no us one. Firstly t he continuo us-time system is discr etig ed in the fusio n center and all t he senso r nodes w it h differ ent sample interv al. T hen the measurement no ises are fo und to be co r related with each other and t he pr o- cess noise tho ugh the no ises of t he co rr espo nding continuo us-time sy st em ar e unco rr elat ed. Finally an asy nchr onous fusion algo r ithm is pr esented for the cor r elat ed noises case. Simulatio n results show t he v alidity o f the presented a lg or ithm)

通信系统仿真中，QPSK调制下的高斯信道Matlab仿真(the simulation of the Gaussian channel in communication system )

多输入多输出系统的多用户信号盲分离MATLAB程序。(multiple-input multiple-output system of multi-user Blind Signal Separation MATLAB program.)

改进的微分先行PID控制算法仿真源程序。 适用于输入信号跳变剧烈的场合，避免骤升或骤降时引起的系统震荡。(Improved differential forward PID control algorithm simulation source. Applied to the input signal transitions dramatic occasions, to avoid swells or sags caused when the system oscillation.)

此文档主要讲述了MATLAB R2011a的simulink的仿真功能完备详细介绍，还有程序仿真图，有助于MATLAB用于仿真的学习(This document focuses on the function of the MATLAB R2011a simulink simulation complete details, there is a program simulation diagram helps MATLAB for simulation learning)

用于数字信号处理教学中的基于simulink的实例(The examples provided in this file can be used to teach signal processing courses.)

这是一个关于MATLAB的很好的学习教程，包括了最基本的语法，怎样编程等很好。(It is a good learning MATLAB-tutorial, including the most basic grammar, how good programming.)

kalman滤波与粒子滤波比较！跟踪slam(Comparison of kalman filter and particle filter! Tracking slam)