unbalanced

calculating time averages in probabilistic manner

Matlab编程实例,合适初学者学习,参考,编程,仿真,很有价值的 (2008-02-14,Matlab)(Matlab programming examples, suitable for beginners to learn, reference, programming, simulation, great value (2008-02-14, Matlab))

该程序是针对智能小车躲避障碍物而设计的，小车通过检测其前方所行进道路上是否有障碍物而判断其运行路线，以能够成功躲避障碍物。(The program is designed for smart car avoid obstacles, the car through the test, the marching on the road if there are obstacles and determine the route operation, and to avoid obstacles to success. )

caculates the ber for CBPSK, DPSK, and Coherent GMSK for fading and no fading usinganalytical means.

由于Matlab不同于其它编程语言,因此在使用数据库方面和其它语言有显著不同.主要介绍 Matlab中数据库的连接和使用。(Because Matlab is different from other programming languages, so in the use of databases and other languages are markedly different. Mainly Matlab database connection and use.)

dsb通信系统调制程序调制载波的波形和频谱分析(dsb demolution)

说明：  基于dwt的水印图像matlab代码，这是小波变换的经典算法(Dwt-based image watermarking matlab code, which is a classical algorithm for wavelet transform)

排队论模型简述，相关实例及拓展的matlab例程(Queuing theory model briefly, relevant examples and expansion matlab routines)

T=[1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1] 输入向量的最大值和最小值 threshold=[0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1] net=newff(threshold,[31 3],{ tansig , logsig }, trainlm ) 训练次数为1000，训练目标为0.01，学习速率为0.1 net.trainParam.epochs=1000 net.trainParam.goal=0.01 LP.lr=0.1 net = train(net,P,T) 测试数据，和训练数据不一致 P_test=[0.2101 0.0950 0.1298 0.1359 0.2601 0.1001 0.0753 0.0890 0.0389 0.1451 0.0128 0.1590 0.2452 0.0512 0.1319 0.2593 0.1800 0.0711 0.2801 0.1501 0.1298 0.1001 0.1891 0.2531 0.0875 0.0058 0.1803 0.0992 0.0802 0.1002 (T = [1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1] ' of the maximum and minimum input vector threshold = [0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1] net = newff (threshold, [31 3], {' tansig' , ' logsig' }, ' trainlm' ) training times for the 1000 target of 0.01 training, learning rate of 0.1 net.trainParam.epochs = 1000 net. trainParam.goal = 0.01 LP.lr = 0.1 net = train (net, P, T) test data, and training data inconsistencies P_test = [0.2101 0.0950 0.1298 0.1359 0.2601 0.1001 0.0753 0.0890 0.0389 0.1451 0.0128 0.1590 0.2452 0.0512 0.1319 0.2593 0.1800 0.0711 0.2801 0.1501 0.1298 0.1001 0.1891 0.2531 0.0875 0.0058 0.1803 0.0992 0.0802 0.1002 )

搜索算法是利用计算机的高性能来有目的的穷举一个问题的部分或所有的可能情况，从而求出问题的解的一种方法(search algorithm is the use of high-performance computer to a purpose of an exhaustive part or all of the possible , and to obtain the solutions of the problems a method)