power_wind_dfig1

The file is about soft sensors in industrial applications.

Galerkin方法,这是一种真正的无网格方法.这种方法采用移动最小二乘函数采近似解变量,并且采用移动最小二乘近似函数的权函数作为加权残值法的权函数.文中对形成的离散动力学方程用Newmark方法求解(Galerkin method, this is a real meshless method. This method adopts moving least squares in function approximation solution variables, and adopts moving least squares approximate function of weight function as a weighted residual method of weight function. In the paper, the discrete dynamic equation formed with Newmark method to solve)

用遗传算法GA优化RBF神经网络，对柴油机进行故障诊断(Optimization RBF neural network using genetic algorithm GA, diesel engine troubleshooting)

matlab的数值分析的程序实现，，又需要的拿啊，，，(matlab numerical analysis of the implementation of procedures, and take the necessary ah,,,)

基于MATLAB的一种雷诺方程的数值解法，包括MATLAB程序(A MATLAB-based numerical solution of Reynolds equation, including the MATLAB program)

系统仿真了HSDPA中的harq系统，对HARQ系统的吞吐量，重传次数做了分析描述 turbo 码matlab编译码程序，包括map和siso译码算法(Simulation of HSDPA in harq system, HARQ throughput of the system, the number of retransmissions to do the analysis described decoding turbo code matlab procedures, including map and siso decoding algorithm)

心电信号的采集与处理 频谱分析与特征提取(ECG acquisition and processing of spectrum analysis and feature extraction)

matlab code for EmbeddingDimension_cao

In this paper, we introduce a new machine-learning-based data classification algorithm that is applied to network intrusion detection. The basic task is to classify network activities (in the network log as connection records) as normal or abnormal while minimizing misclassification. Although different classification models have been developed for network intrusion detection, each of them has its strengths and weaknesses, including the most commonly applied Support Vector Machine (SVM) method and the Clustering based on Self-Organized Ant Colony Network (CSOACN). Our new approach combines the SVM method with CSOACNs to take the advantages of both while avoiding their weaknesses. Our algorithm is implemented and evaluated using a standard benchmark KDD99 data set. Experiments show that CSVAC (Combining Support Vectors with Ant Colony) outperforms SVM alone or CSOACN alone in terms of both classification rate and run-time efficiency.

topsis college selection