face_detection

说明：  平面板杆结构有限元分析，包中有详细的WORD文档说明(Flat panel rod finite element analysis)

MATLAB_SIMULINK在电力系统工程仿真中的应用，本书对电力系统仿真的各元器件进行了详细的介绍，同时采用大量案例，学习simulink在电力系统仿真很容易上手。(MATLAB_SIMULINK in power systems engineering simulation applications, this book on the power system simulation carried out for each component in detail, while using a large number of case study in the power system simulation simulink very easy to use.)

捕鱼策略中MATLAB源代码 捕鱼策略中MATLAB源代码(OPTIMAL STRATEGY OF FISHING OPTIMAL STRATEGY OF FISHING)

The firefly algorithm (FA) is a metaheuristic algorithm, inspired by the flashing behaviour of fireflies. The primary purpose for a firefly s flash is to act as a signal system to attract other fireflies. Xin-She Yang formulated this firefly algorithm by assuming:[1] All fireflies are unisexual, so that one firefly will be attracted to all other fireflies Attractiveness is proportional to their brightness, and for any two fireflies, the less bright one will be attracted by (and thus move to) the brighter one however, the brightness can decrease as their distance increases If there are no fireflies brighter than a given firefly, it will move randomly. The brightness should be associated with the objective function. Firefly algorithm is a nature-inspired metaheuristic optimization algorithm.

Convert SRH model outputs into an SMS

说明：  曲线拟合 matlab 毕业设计常用 (use matlab curve fitting )

have players give the function of song category, there is fast forward, pause, stop

说明：  全文目录包括： 1、绪论 2、编程基础 3、概率论与数理统计基础 4、蒙特卡洛原理 5 粒子滤波原理 6 改进粒子滤波算法 7 粒子滤波在目标跟踪中的应用 8 粒子滤波在电池寿命估计中的应用(Full text catalog includes: 1. Introduction 2.Fundamentals of programming 3. Probability theory and basis of mathematical statistics 4. Monte Carlo principle 5 principle of particle filter 6. Improved particle filter algorithm 7. Application of particle filter in target tracking 8. Application of 8 particle filter in battery life estimation)

最大值分割图像边缘提取子程序最 大值分割图像边缘提取子程序(Image Edge Detection maximum partition partition maximum Subroutine Subroutine Image Edge Detection)

he basic idea of the method of bisection is to start with an initial interval, [a0,b0], that is chosen so that f(a0)f(b0) < 0. (This guarantees that there is at least one root of the function f(x) within the initial interval.) We then iteratively bisect the interval, generating a sequence of intervals [ak,bk] that is guaranteed to converge to a solution to f(x) = 0.