速度波门拖引干扰原理

对图像进行重构，主要用于穿透散射介质的目标成像恢复与实验研究(Image Reconstruction)

这个程序只是简单配置了一下硬件哈，程序也只是简单弄了一下(This program is just a simple configuration of hardware, and the program is just a simple one.)

灰色系统GM（1,1）模型，用于预测分析，简单易懂，条理清晰(Grey System GM(1,1) Model for Prediction and Analysis, Simple and Clear)

ISA总线资料《ISA System Architecture》(ISA System Architecture)

说明：  Problemas de Potencia

说明：  Java语言编写100以内的素数，完整的源代码(Java language to write less than 100 prime Numbers, complete source code)

说明：  为了提升配网供电可靠性的预测精度!提出了基于主成分分析和粒子群优化极限学习机的配网供电可靠 性预测模型$ 从多方面分析影响供电可靠性的指标!利用主成分分析得到综合变量!实现对数据的降维$ 在此基 础上!构建人工神经网络并利用粒子群算法优化极限学习机的输入权值和阈值!完成对训练供电可靠性预测模型 的训练$ 以某大型电网的 ?L 个供电局样本 !% 种影响供电可靠性因素为例进行仿真分析!并将 E S R C E FQ C 4 G D算 法与 ! 种回归拟合算法对比!验证了该方法的有效性(It is clear that the learning speed of feedforward neural networks is in general far slower than required and it has been a major bottleneck in their applications for past decades. Two key reasons behind may be: (1) the slow gradient-based learning algorithms are extensively used to train neural networks, and (2) all the parameters of the networks are tuned iteratively by using such learning algorithms. Unlike these conventional implementations, this paper proposes a new learning algorithm called extreme learning machine (ELM) for single-hidden layer feedforward neural networks (SLFNs) which randomly chooses hidden nodes and analytically determines the output weights of SLFNs. In theory, this algorithm tends to provide good generalization performance at extremely fast learning speed. The experimental results based on a few artificial and real benchmark function approximation and classification problems including very large complex applications show that the new algorithm can p)

本例题是在MATLAB环境下搭建双馈风力发电机的模型，通过解耦控制实现功率的控制。(The sample questions are in the MATLAB environment to build double-fed wind turbine model, through the decoupling control to achieve power control.)

java编程思想源代码，全书代码均在里面。(Java programming thought source code)

说明：  模糊控制算法 做温度跟踪控制 TS模型 matlab开发的模糊控制实例(Fuzzy Control Algorithm for Temperature Tracking Control TS Model)