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说明：  matlab 从入门到精通 很好的一本书(matlab a book)

等间距线性阵列，阵元数M=8，阵元间距d= λ /2，等幅加权，目标方位φr =0°。产生空间白噪声矢量（复高斯分布）。 设阵列信号矢量元素s(m)=exp[j mψr]，其信号幅度为1，该阵元接收机附加的高斯噪声为n(m)=nmr+jnmi，其中实虚部均为独立同分布N(0, σ2)的高斯随机数，则该通道合成信号x(m)=s(m) + n(m)，其中信噪比为： SNR = 10 lg[1/(2σ2)] = – 3 – 10 lg(σ2) (dB) (The spacing of the linear array, and the array element number M = 8, the array element spacing d = λ/2, equal amplitude weighted target azimuth φR = 0. Space generated white noise vector (complex Gaussian distribution). Let array signal vector elements s (m) = exp [j mψr], the signal amplitude, the element receiver additional Gaussian noise n (m) = nmr+jnmi which the real and imaginary parts are independent and identically distributed N ( Gaussian random numbers of 0, σ2), the channel the synthesis signal x (m) = s (m) the PPLS n (m), where SNR is: SNR = 10 lg [1/(2σ2)] =- 3- 10 lg (σ2) (dB))

It is a function of active disturbance reject control

灰色关联算法的MATLAB仿真实现，可用于态势预测(MATLAB simulation gray correlation algorithm, can be used to predict the trend)

本文档是本人的自适应控制大作业，作业里分模型参考自适应控制（用smulink仿真）和CARMA模型的最小方差自适应控制，文中有详细的smulink框图和matlab程序，格式美观，分析透彻，图形整齐，对学习自适应控制的朋友有很大的帮助，谨以本人微薄的力量和成果与大家共鸣，(This document is my adaptive control large operations, operating in sub-model reference adaptive control (with smulink simulation) and the CARMA model of minimum variance adaptive control, the text has a detailed diagram smulink and matlab procedures, aesthetic format, analysis and thorough , graphics, neat, in learning adaptive control of a friend has a great help, I would like my meager results of the strength and resonance with the U.S.,)

CIC滤波器的插值运算，并可以实现数字下变频的整个算法的研究，与仿真(design and simulink )

模糊综合评价法matlab源码,有详细的注释说明，程序中有所需要的实例数据(The fuzzy comprehensive evaluation method matlab source code )

matlab中关于S函数用法的简单示例，帮助初学者快速理清S函数编程格式(simple example on the usage of the S function in the matlab help beginners sort out the S-function programming format)

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参数化时频分析理论、方法及其在工程信号分析中的应用 (THEORY, METHODOLOGY OF PARAMETERIZED TIME-FREQUENCY ANALYSIS AND ITS APPLICATION IN ENGINEERING SIGNAL PROCESSING )