vmdpy-master

说明：  基于MATLAB的四旋翼无人机PD轨迹跟踪算法，能较好地实现轨迹跟踪(PD trajectory tracking algorithm of four rotor UAV Based on Matlab can achieve better trajectory tracking)

ASP系统开发[毕业设计]-ASP system development [ graduation project ]

several parts of AOO source released at 2019 described in several languages.

cadense user book (rar)-cadense user book (240.1)

说明：  2017年10月，图灵奖得主Geoffrey Hinton在机器学习的顶级会议“神经信息处理系统大会(NIPS)”上发表了题为《胶囊之间的动态路由》(Dynamic Routine Between Capsules)的论文，提出了全新的深度学习方法——胶囊网络(In October 2017, Turing prize winner Geoffrey Hinton published a paper entitled "dynamic routing between capsules" at the top conference of machine learning "nips", and proposed a new deep learning method capsule network)

基于PSCAD仿真软件的光伏发电系统模型实例，fortran语言(The example of photovoltaic power generation system model)

实现自适应LMS滤波的功能，LMS 自适应滤波器在噪声消除方面具有很好的效果 ,且在信噪比较小的情况下也可以完成一定条件下的数字滤波任务。(To realize the function of adaptive LMS filtering, the LMS adaptive filter has a good effect in noise elimination, and the digital filtering task under certain conditions can be completed under the condition of small signal-to-noise ratio.)

英培特嵌入式开发系统IDE软件包，包括软件仿真功能，是ARM开发的好帮手-British tissue culture embedded system development IDE package, including software simulation function, the development of the ARM is a good helper

VisualC#.net基础与应用教程（第2版）课后习题第五章第八题、设计黑白棋游戏程序。(Visual C# .net Basic and Application Course (2nd Edition) Exercise Chapter 5, Question 8, Design black and white chess game program.)

说明：  粒子群算法，也称粒子群优化算法或鸟群觅食算法（Particle Swarm Optimization），缩写为 PSO， 是由J. Kennedy和R. C. Eberhart等开发的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法(Particle Swarm Optimization (PSO), also known as Particle Swarm Optimization (PSO), is a new evolutionary algorithm developed by J. Kennedy and R. C. Eberhart. PSO is a kind of evolutionary algorithm, which is similar to simulated annealing algorithm. It starts from random solution and searches for the best solution by iteration. It also evaluates the quality of solution by fitness. But it is simpler than genetic algorithm rules. It has no Crossover and Mutation operation of genetic algorithm. As a result, it searches for global optimum by following the optimal value currently searched. This algorithm has attracted the attention of academia for its advantages of easy implementation, high accuracy and fast convergence, and has shown its superiority in solving practical problems. Particle swarm optimization is a parallel algorithm)