finity2D

利用ARIMA处理分析时间序列，计算数列相关性和数字特征并通过计算所得值进行一定范围的预测(ARIMA processing analysis time sequence, to calculate a number of columns and digital characterized by the calculated value for a certain range of the prediction)

递归神经网络-实时学习训练算法代码，亲测可用，简洁无误，容易上手。( Recursive neural network- real-time learning training algorithm code, pro-test available, simple and correct, easy to use.)

数据模型归一化，模态振动，分析了该信号的时域、频域、倒谱，循环谱等,用于信号特征提取、信号消噪。( Normalized data model, modal vibration, Analysis of the signal time domain, frequency domain, cepstrum, cyclic spectrum, etc. For feature extraction, signal de-noising.)

这是利用C++ 编的fft(This is the C series fft)

主要用于计算半导体激光器调制的程序；可以针对常用的半导体激光器的调制进行数值分析(mainly used in the calculation of the semiconductor laser modulation procedures; can address common semiconductor laser modulation Numerical Analysis)

用传输矩阵法计算一维光子晶体的带结构的程序,用matlab所编,文件解压后,程序写在word文档中,并附有在matlab下画的图,本人感觉非常有用(use of the transfer matrix method one-dimensional photonic crystal with the structure of the program, prepared by Matlab. unpacks the files, procedures written in word document, together with the painting under Matlab plans, I feel very useful)

一个基础贝叶斯变换的压缩感知，包含一个源代码和一个一维信号处理的例子和两个二维图像的例子(The basic BCS implemented via a variational Bayesian approach. The package includes the core VB-BCS code, one example of a 1-dimensional signal and two examples of 2-dimensional images.)

使用matlab进行 有限元计算，内含多种方式方法，欢迎交流讨论(Finite element calculation using matlab)

ABAQUS 有限元子程序，粘弹性本构，蠕变应力松弛测试拟合结果(ABAQUS umat creep stress relaxation fitting result)

针对多径效应的影响，提出了一种基于矩阵束的MIMO 雷达低仰角快速估计方法。该方法同时考虑了发射多径信号和接收多径信号，采用单样本数信号矢量构造了一个前后向矩阵束，并利用两个酉矩阵对该矩阵束进行降维处理，最后采用广义特征值分解的总体最小二乘法来估计目标角度。算法不需要估计数据协方差矩阵，可在低 信噪比和单样本数情况下，有效地克服多径效应，实现同时多目标低仰角估计，相比最大似然算法，避免了谱峰搜索，计算量小。仿真结果验证了该算法的有效性。(To overcome the multipath effect, a fast algorithm for low elevation estimation for MIMO radar via matrix pencil is proposed. The signals both in transmit multipath and receive multipath are considered. Firstly, a forward-backward matrix pencil is formed based on the single-sampled vector. Secondly, the reduced-dimensional processing is applied to the matrix pencil via two unitary matrices. Finally, the generalized eigen-decomposition is employed to estimate the low elevation in multipath environments directly. Without the covariance matrix estimation, the proposed method can overcome multipath effect effectively in case of low SNR and estimate multi-target simultaneously. Compared with Maximum Likelihood (ML) method, it avoids spectrum peak searching and reduces the computational burden. Numerical results verify the effectiveness of this method)