SHUZHIFENXI

FFT with fix point 2*N

对于空间上的任意几个点所在的直线或曲线，该程序可以拟合出的方程。(For any of several points on the space where the line or curve, the program can fit out of the equation.)

说明：  一帧语音+CS(MP,BP OMP)重构算法包括读取分帧重构计算 误差分析(A voice+CS (MP, BP OMP) reconstruction algorithm consists of reading framing error analysis reconfigurable computing)

说明：  二级转运站选址数学规划模型求解的lingo 程序(Lingo Program for Solving Mathematical Programming Model of Secondary Transfer Station Location)

c++编写的小波包算法，可以实现小波包分解与重构，速度较快(A wavelet packet implementation written in C++, does wavepacket decomposition and reconstruction quite efficiently)

非线性振动.pdf 刘延柱编写 恢复力与位移不成正比或阻尼力不与速度一次方成正比的系统的振动。尽管线性振动理论早已相当完善,在工程上也已取得广泛和卓有成效的应用，但在实际问题中，总有一些用线性理论无法解释的现象。一般说，线性模型只适用于小运动范围，起出这一范围，按线性问题处理就不仅在量上会引起较大误差，而且有时还会出现质上的差异，这就促使人们研究非线性振动。(Nonlinear Vibration. Compilation of PDF Liu Yanzhu)

相变UDF，包括质量传递和热量传递，能够进行气液相变的模拟(Phase transition UDF, including mass transfer and heat transfer, gas-liquid phase transition can be simulated)

频域二维卷积算法，通过在频域用fft计算，加速了卷积的实现过程(Frequency domain of two-dimensional convolution algorithm, by calculating the frequency domain using fft and accelerate the realization of the convolution process)

说明：  对该模型参数辨识采用递推最小二乘法，即 RLS（ recurisive least square）， 它是一种能够对模型参数进行在线实时估计的辨识方法。(The recursive least square method is used to identify the parameters of the model, that is, rls (recurisive least square), which is an online real-time estimation method for the model parameters)

用切比雪夫多项式逼近已知函数 用勒让德多项式逼近已知函数 用帕德形式的有理分式逼近已知函数 用列梅兹算法确定函数的最佳一致逼近多项式 求已知函数的最佳平方逼近多项式 用傅立叶级数逼近已知的连续周期函数 离散周期数据点的傅立叶逼近 用自适应分段线性法逼近已知函数 用自适应样条逼近（第一类）已知函数 离散试验数据点的多项式曲线拟合 离散试验数据点的线性最小二乘拟合 离散试验数据点的正交多项式最小二乘拟合 (By using Chebyshev polynomial approximation of the known functionApproximation of the known functions by Legendre polynomialsApproximation by rational fraction of known function in the form of PadmaTo determine the best uniform function polynomial approximation with the Lemez algorithmThe best known polynomial square for function approximationContinuous periodic function with Fourier series approximation of the knownApproximation of discrete data points in the Fu Liye cycleApproximation of the known function with adaptive piecewise linear methodAdaptive spline approximation ( first class ) known functionPolynomial curve fitting of discrete data pointsLinear least squares fitting of discrete data pointsOrthogonal polynomial least squares fitting of discrete data points)