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tsp问题 一些经典的MATLAB程序 模拟退火算法 遗传算法 望高手指几点(tsp)

really understand,describe using matlab

periodogram in a white noice

自举是一种由重采样估计，独立和（蒙特卡洛重采样）等概率设置一个单一的数据统计变化的一个途径。允许的措施估计那里的潜在分布是未知的或者样本量很小。他们的结果与这些分析方法的统计特性相一致。 在这里，我们使用非参数逼近。非参数引导更简单。它不使用该模型的结构，建造人工数据。矢量[易西]是重采样，而不是直接与replecement。这些参数是从这些对构建。 二，回归模型时，应使用在回归方程中的两个变量是随机的，会有错误的，即不是由研究者控制。模式，我用普通最小二乘回归低估了变量之间的错误时，他们都含有线性关系的斜率。据索卡尔和罗尔夫（1995），模型二回归的主题是一对哪些研究和争论仍在继续，最终建议是很难做出。 BOOTGMREGRESS模型II是一个引导程序。这需要s引导和规范样品前坡计算变量。这两个变量的每个转化为具有零均值和标准差的一个。由此产生的斜率是线性回归系数的Y在X里克创造了这个词（1973）几何平均数并给出了一个模型II回归广泛审查。它也被称为引导标准的主要轴线(The bootstrap is a way of estimating the variability of a statistic from a single data set by resampling it independently and with equal probabilities (Monte Carlo resampling). Allows the estimation of measures where the underlying distribution is unknown or where sample sizes are small. Their results are consistent with the statistical properties of those analytical methods. Here, we use the Non-parametric Bootstrap. Non-parametric bootstrap is simpler. It does not use the structure of the model to construct artificial data. The vector [yi, xi] is instead directly resampled with replecement. The parameters are constructed from these pairs. Model II regression should be used when the two variables in the regression equation are random and subject to error, i.e. not controlled by the researcher. Model I regression using ordinary least squares underestimates the slope of the linear relationship between the variables when they both contain error. According to Sokal and Rohlf (1995), t)

本程序是运用小波分析和神经网络结合方法进行风速预测(This procedure is the use of wavelet analysis and neural network approach to predict wind speed)

1、 生成多周期线性调频信号，并对其进行频谱分析； 2、 对仿真生成的信号利用两种窗口函数进行STFT变换生成时频分析图(1, to generate multi-cycle chirp signal, and its spectrum analysis 2, the signal generated by the simulation window function using two STFT transform to generate time-frequency analysis chart)

finite-time稳定控制算法，李雅普诺夫方法得出LMI算法，进而求出反馈增益矩阵(finite-time stability control algorithm)

method for speech enhancement

模式识别中的bayes判别分析算法，进行逐步线性回归，小波包分析提取振动信号中的特征频率。( Pattern Recognition bayes discriminant analysis algorithm, Stepwise linear regression, Wavelet packet analysis to extract vibration signal characteristic frequency.)

智能天线程序,关于天线的方向图,和方向因子,增益等仿真(Smart antenna program on the antenna pattern, and direction factor, gain, etc. Simulation)