multi-kernels-SVR

使用“改进的欧拉公式”和“4阶龙格-库塔公式”分别对Volterra方程求解，绘制解曲线、相轨线，并将结果进行比较。(Using the " improved Euler formula" and " 4-order Runge- Kutta formulas," respectively, Volterra equations, draw solution curves, phase trajectories, and the results were compared.)

C++反射的一种简单实现 A simple way to make cpp reflection real(A simple way to make cpp reflection real)

中心逼近式改进灰色模型滑坡形变预测预报代码，自己写的，带有详细的解释(Center approach to improve the gray model of landslide deformation forecasting code, wrote it myself, with a detailed explanation)

该Matlab算法，可以实现振动数据的文件的读取，进而可以进行时频分析，得到信号特征值(The Matlab algorithm can achieve vibration data of the document read, in turn, can be time-frequency analysis, Signal Characteristics)

matlab matlab source code lic lice

一个很有意思的小程序，可以用于向对方表白哦。(A very interesting small program that can be used to declare each other oh.)

定位技术是无线传感器网络中关键的基础支撑技术, 目前提出了许多静态网络的节点定位算 法, 移动无线传感器网络的定位研究相对较少. 针对定位节点和参考节点随机运动的网络模型, 提出了 一个基于动态网格划分的蒙特卡罗定位算法. 算法中当接收的参考节点数超过一定阈值时使用最远距 离节点选择模型, 选出部分参考节点参与定位和信息转发, 节约能耗. 接着基于选择的或所有接收的参 考节点构建采样区域, 进行网格划分, 使用网格单元数计算最大采样次数, 在采样区域内采样并使用误 差补偿的运动模型进行过滤, 提高了采样效率, 减少了计算开销, 并保证了较好的定位精度. 仿真实验表 明算法在定位精度, 计算开销、能耗等方面都具有较好的性能.(Positioning technology is critical in wireless sensor networks based supporting technologies, currently made many static network node localization algorithms, the positioning of mobile wireless sensor network research is relatively small. Locate node and a reference node for random motion network model, proposed a Dynamic meshing based Monte Carlo localization algorithm. algorithm when the received reference nodes exceeds a certain threshold, the most distant node selection model selects some reference nodes involved locating and forwarding information, save energy. then based on the selection or building all received reference node sampling area, meshing, the number of grid cells used to calculate the maximum sampling frequency, the sampling area sampling and using motion model error compensation filter to improve sampling efficiency, reducing the computational overhead and to ensure a better positioning accuracy. Simulation experiments show that the algorithm in positioning accuracy,)

统计信号处理中，计算双谱的仿真程序，已通过测试。(Bispectrum calculation procedures.)

Newton-Armijo code for scalar equations: Inputs: X = initial iterate, F = function, TOLA = absolute error tolerance, TOLR = relative error tolerance, JDIFF = 0, analytic derivative, syntax: [f,fp]=f(x), JDIFF = 1, forward difference derivative , Output: x=approximate result, HIST = array of iteration history

说明：  现代信号处理中对基本的ESPRIT的一种改进算法的程序，并利用算法进行了信号频率的统计仿真实验！(Modern signal processing of basic ESPRIT An Improved Algorithm for the procedures and the use of algorithms of statistical signal frequency simulation!)