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In this example we solve the following single ODE Program Name: RKG-1.FOR (Runge-Kutta-Gill algorithm, fixed step size)

This application not only demonstrates the basics of using the Microsoft Foundation classes but is also a starting point for writing your application.

MIDlet通过蓝牙与电脑通信的案例,This resource demonstrates how to create Java&#8482 applications that use Bluetooth communication between a PC and a mobile device. The document focuses, from Java programming point of view, on how to configure and use two alternative PC-side solutions: COM-based and J ...

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消息中间件(Message—OrientedMiddleware，简称MOM)提供客户和服务器的同步和异步连接，并且在任意的时刻对消息进行传送和存储转发。消息的传输一般都支持Point—to—Point模式和Publish／Subscribe模式。消息中间件为大规模分布式环境下应用程序的集成提供了一种有力的集成工具。越来越多的分布式应用采用消息中间件，通过 ...

// // Histogram Sample // This sample shows how to use the Sample Grabber filter for video image processing. // Conceptual background: // A histogram is just a frequency count of every pixel value in the image. // There are various well-known mathematical operations that you can perform on an image ...

北京大学ACM题 Here is a geometric problem. You have an angle and some squares in the first quadrant of the plane rectangular coordinates. The vertex of the angle is fixed on the origin O of the coordinates, and both of its radial lines are specified by the input. The sizes of the squares are also s ...

KMEANS Trains a k means cluster model.CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-means algorithm to set the centres of a cluster model. The matrix DATA represents the data which is being clustered, with each row corresponding to a vector. The sum of squares error function is used. The ...

Hybrid Monte Carlo sampling.SAMPLES = HMC(F, X, OPTIONS, GRADF) uses a hybrid Monte Carlo algorithm to sample from the distribution P ~ EXP(-F), where F is the first argument to HMC. The Markov chain starts at the point X, and the function GRADF is the gradient of the `energy function F.

遗传算法和“货郎担” 问题: "The traveling salesman problem, or TSP for short, is this: given a finite number of cities along with the cost of travel between each pair of them, find the cheapest way of visiting all the cities and returning to your starting point."