travelling salesman problem using genetic algorithm

NumericalMethods in Engineering withMATLAB® is a text for engineering students and a reference for practicing engineers, especially those who wish to explore the power and efficiency of MATLAB. The choice of numerical methods was based on their relevance to engineering problems. Every method is discussed thoroughly and illustrated with problems involving both hand computation and programming. MATLAB M-files accompany each method and are available on the book web site. This code is made simple and easy to understand by avoiding complex book-keeping schemes, while maintaining the essential features of the method. MATLAB, was chosen as the example language because of its ubiquitous use in engineering studies and practice. Moreover, it is widely available to students on school networks and through inexpensive educational versions.MATLAB a popular tool for teaching scientific computation.

low pass filter design using matlab

BP神经网络代码，使用LM算法（高斯牛顿法的改进，具有很好的鲁棒性）(BP neural network code, use the LM algorithm (modified Gauss-Newton method has good robustness))

用matlab进行小波分析，代码中有关于小波分析的高级技术(Advanced Technology on wavelet analysis wavelet analysis using matlab code)

这是matlabdaima,用来计算RBF输出值很有效(This is matlabdaima, used to calculate the RBF output is valid)

二维TE波的FDTD的实现，采用MUR吸收边界条件。(2D TE wave of FDTD the realization used MUR absorbing boundary conditions.)

灰色verhust模型的matlab程序在给定一组序列的情况下求得其预测值，残差，相对误差(Gray verhust model matlab program to obtain their predictive value, residuals, the relative error in the sequence of a given set of circumstances)

经典的leach算法，参考sep原文更容易看懂(the classic wsns algorithm，leach)

MUSIC算法是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成。MUSIC算法就是利用这两个互补空间之间的正交特性来估计空间信号的方位。噪声子空间的所有向量被用来构造谱，所有空间方位谱中的峰值位置对应信号的来波方位。MUSIC算法大大提高了测向分辨率，同时适应于任意形状的天线阵列，但是原型MUSIC算法要求来波信号是不相干的。(MUSIC algorithm is a matrix decomposition method based on feature space. From the geometric point of view, the observed spatial signal processing can be decomposed into signal subspace and noise subspace, it is clear that the two spaces are orthogonal. The signal received by the array to the subspace of the covariance matrix of the signal component corresponding eigenvectors, the noise subspace of the covariance matrix of all by the smallest eigenvalue (noise variance) eigenvectors corresponding to the composition. MUSIC algorithm is the use of orthogonal properties between these two complementary space to estimate the spatial orientation of the signal. Noise subspace of all vectors are used to construct the spectrum, all the spatial orientation of the spectrum corresponding to the peak position of the signal wave direction. MUSIC algorithm greatly improves the resolution measurements, while the antenna array adapted to any shape, but the prototype MUSIC algorithm requires to wave sign)

Program to simulate arbitrary classical billiard systems.