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本压缩文件里面的程序是LMFnlsq2.rar里面主程序调用的一个函数，此函数不可或缺，需要联合使用。(This program inside the compressed file is LMFnlsq2. Rar inside the main program calls a function, this function is indispensable, need to use.)

该程序能够实现小球的运动，且小球运动角速度可调，单击【开始】，小球开始运动。(The program is able to achieve a small movement of the ball and ball movement angular velocity is adjustable, click [Start], the ball starts to move.)

本代码是基于MATLAB开发的，主要用于仿真基于QPSK调制的OFDM信号。(OFDM QPSK)

计算目标和海洋回波的功率谱密度,该函数用来计算任意函数的一阶偏导数(数值方法),迭代自组织数据分析。( Calculating a target and ocean echo power spectral density, This function is used to calculate the arbitrary function of the first order partial derivative (numerical methods), Iterative self-organizing data analysis.)

用FDTD仿真电源-地同步澡声，计算了反射，透射系数(applies finite difference time domain method to analyze transmission coefficient.)

Claypol book FEM Source code in MATLAB

DFT进行频谱分析时的三种现象 1、混叠：对连续信号采样，要求连续信号是带限的，采样频率要足够高。Fs应满足Nyquist采样定理才不产生混叠。 采样前加低通滤波器防混叠 2、频谱泄漏：DFT对时域信号进行了截断（相当于采样信号乘了一个窗函数），时域的乘积相当于频域卷积，改变了原信号频谱。 改用其他窗函数（非矩形）改善泄漏。 3、栅栏现象：DFT 只给出了频谱在采样点上的取值，采样点间的频谱内容丢失。(DFT spectrum analysis of a three phenomena, aliasing : continuous signal sampling, requiring continuous signal is band-limited, the sampling frequency should be high enough. Fs meet the Nyquist Sampling Theorem would not have aliasing. Sampling former low-pass filter plus anti-aliasing 2, spectrum leakage : DFT right time domain signal a disconnect (equivalent to a sampling signal by a window function). time domain is equivalent to the product of frequency-domain convolution, changes in the spectrum of the original signal. Window functions to switch to other (non-rectangular) to improve leakage. 3, fenced phenomenon : DFT spectrum is given only at the sampling point value, sampling points of the spectrum as lost.)

This book is useful for writing a standard report, paper.

sar图像成像仿真（包括rd算法，cs算法，rdm算法，内含sinc插值法距离徙动校正）。(-RD algorithm---- SAR point target simulation results is quite good.)

说明：  频谱分析 自己写的 可以给大家参考 学习学习(Spectrum analysis, written by myself, can give you reference, learning and learning)