barkercode

matlab 和 c 实现的 sift 算法(the excutable code implemented by matlab and c of sift algorithm)

能实现导航，路线规划，可增加途径点后在进行导航，也可直接导航(To achieve navigation)

A simple Butterword filter

Sphit算法针对１２８*１２８的灰度图象进行压缩处理，经典算法，可以任意改进()

空间梁验证算例 算例1 计算一空间圆杆形悬臂梁，截面尺寸为，直径 厘米，长度 米，弹性模量 质量密度 。 (Spatial beam validation example calculation of a space for example a rod-shaped cantilever beam, cross-sectional size, diameter cm, length m, elastic modulus, mass density.)

加窗函数的FIR数字滤波器设计的matlab实例(FIR digital filter design windowing function matlab examples)

读取txt文本文件中的数据，然后自动画滞回曲线图！可以区分不同周期，用不同颜色描述！(Txt text file to read the data, then the hysteresis curve from the animation! Can distinguish between different periods, with different color descriptions! )

The generating systems use Doubly-Fed Induction Generators (DFIGs) to achieve high conversion efficiency and to reduce the installation cost. This paper presents a modeling and Maximum Power Point Tracking (MPPT) control method of DFIG-based variable-speed wind energy conversion system. The generator considered is a wound rotor induction machine whose stator is connected directly to the grid and the rotor is fed through back-to-back Pulse-Width Modulation (PWM) converters. Stator flux-oriented vector control is applied to control the active and reactive current loops independently. The MPPT control method in a Wind Energy Conversion System (WECS) is proposed. The proposed control solution aims at driving the position of the operating point near to optimality. This is a very important aspect to maintain DFIGs efficiently in a variable wind speed. The wind generator is modeled in RSCAD program which is interfaced with the Real Time Digital Simulator (RTDS).

这是一个经典的形变模型实施,在一个单一的文件用简单的可以理解的代码。 功能包括两部分一个简单的弱分类器和一个促进部分: 弱分类器试图找到最佳阈值的数据维数对数据进行分离成两个阶级1和1 要求的进一步提高分类器部分迭代,每一步是变化分类权重miss-classified例子。这造成了一连串的“弱分类器”,表现得像一个“强大分类器” (This a classic AdaBoost implementation, in one single file with easy understandable code. The function consist of two parts a simple weak classifier and a boosting part: The weak classifier tries to find the best threshold in one of the data dimensions to separate the data into two classes-1 and 1 The boosting part calls the classifier iteratively, after every classification step it changes the weights of miss-classified examples. This creates a cascade of "weak classifiers" which behaves like a "strong classifier" . )

基于matlab的边缘检测源程序 基于matlab的边缘检测源程序 基于matlab的边缘检测源程序(Matlab-based edge detection source)