Power-System-Simulation-with-Matlab-(Simulink)

混沌生成的很多公式，混沌生成的很多共式，混沌生成的很多形式(Formula generated a lot of chaos, chaos generated a lot of a total style, chaos generated many forms)

说明：   本文在研究IEEE802.16e协议和SIP协议的基础上，提出了利用 SIP解决IEEE802.16接入网络中端到端切换的新方案。该方案采用跨 层切换的设计思想，联合MAC层和应用层SIP协议，在底层链路切换 的同时，完成应用层会话的修改，加快了切换过程，减少了切换时延， 提高了切换成功率。本文基于NS2仿真平台，完成了相应的仿真平台 搭建过程，实现了SIP协议模块和WiMAX协议模块的融合，扩展了SIP 协议模块的部分消息，最终在基于SIP协议模块和WiMAX协议的统一 NS2平台上实现了基于WiMAX接入、支持SIP扩展功能的SIP会话建 立和修改过程。 ( On the basis of study of WiMfAX and SIP, a new mechanism using SIP to achieve end-to-end handoff under IEEE802.16e access networks is Ob proposed handoffs, in this thesis. The mechanism adopts a cross-layer design which means that the l}iIAC layer handoff procedure can interleaved with that of the application layer. During the handoff at link )

含NWP数值天气预报和不含NWP数值天气预报的BP神经网络预测风电功率两种方法进行比较，含数据，实际案例。(With and without NWP NWP Numerical Weather Prediction NWP BP neural network prediction of wind power are two methods were compared with the data, the actual case.)

理想流体势无网格伽辽金法二维程序，EFG法(Ideal fluid Potential free Galerkin method D program, EFG method)

matlab仿真bpsk的源代码，很有参考价值的(BPSK simulation matlab source code, are worthy of)

computing Mutual information estimation of a mixture sounds

The proportional–integral–derivative controller consists of three simple actions, i.e. P, I, and D actions.

包括无监督和监督的机器学习技术 • K-means and other clustering tools • Neural Networks • Decision trees and ensemble learning • Naï ve Bayes Classification • Linear, logistic and nonlinear regression(Highlights include unsupervised and supervised machine learning techniques including: • K-means and other clustering tools • Neural Networks • Decision trees and ensemble learning • Naï ve Bayes Classification • Linear, logistic and nonlinear regression)

gabor变换matlab程序 可以做地震数据频谱分析(Gabor transform MATLAB program can do seismic data spectrum analysis)

matlab小波分析程序，实现了图像的加水印，去噪，加噪声等功能，BP神经网络的整个训练过程。( matlab wavelet analysis program, Realize image watermarking, de-noising, plus noise and other functions, The entire training process BP neural network.)