s_parmos_release_version_10b

说明：  GONZALEZ数字图像处理第二版习题解答（英文版）(GONZALEZ Digital Image Processing Second Edition Problem Solutions (English))

ICA算法评价指标的计算程序SAR SIR SNR(ICA SAR SIR SNR)

An Introduce To dynamical system

基于matlab的指纹库识别，指纹识别(matlab)源代码。(Matlab-based fingerprint database recognition, fingerprint recognition matlab source code.)

This paper presents a new and efficient approach for capacitor placement in radial distribution systems (RDS) that determine the optimal locations and size of capacitor with an objective of improving the voltage profile and reduction of power loss. The solution methodology has two parts: in part one the loss sensitivity factors (LSF) are used to select the candidate locations for the capacitor placement and in part two a new algorithm that employs Dijkstra Algorithm (DA) is used to estimate the optimal size of capacitors at the optimal buses determined in part one. The main advantage of the proposed method is that it does not require any external control parameters. The other advantage is that it handles the objective function and the constraints separately. The proposed method is applied to 33 & 69 RDS. The solutions obtained by the proposed method are compared with other methods. The proposed method has outperformed the other methods in terms of the quality of solution. OPTIMAL C

说明：  微电网虚拟同步发电机控制的MATLAB例子，simulink可以运行(Matlab example of micro grid virtual synchronous generator control, Simulink can operate.)

matlab nrs程序，含泪共享，需要的下载吧(matlab nrs procedures, sharing tears, need to download it)

说明：  LSTM简单例程及源程序，LSTM例程，源程序(LSTM routines, source code)

说明：  主元分析方法（PCA）是一种基于多元统计分析的数据降维方法, 它利用过程变量间的相关关系, 建立正常工况下的主元模型, 通过检验新的数据样本相对于主元模型的背离程度, 从而发现异常和故障。 (Principal Component Analysis (PCA) is based on multivariate statistical analysis of the data reduction method, which uses the correlation between process variables and establish the normal condition of the main element model, by testing samples of the new data relative to the principal component model departure from, and thus abnormal and failure.)

calssification algorithm1