MATLAB

模拟退火算法TSP matlab实现(Simulated annealing algorithm realize TSP matlab)

利用matlab编写的程序，用于音乐播放青花瓷(the function to display songs based on matlab)

使用C和Matlab编程实现感知器算法和最小平方误差算法，并且区分给定的10000个样本(C and Matlab programming Perceptron algorithm and least square error algorithm, and to distinguish between a given sample 10000)

雷达多目标检测方面的程序，针对不同目标，根据回拨信息的的不同进行目标分析得到目标方位估计。(It useful for the new learner)

使用matlab编程进行工程计算如解线性方程组或者进行数值计算的方法(the use of matlab to accomplish engineering calculations such as solving linear equations or numerical calculation)

QAM调制软比特解调，能够更准确进行解调。(Soft bit QAM modulation and demodulation, can be more accurately demodulated.)

图像处理目标识别程序 源码网上下载的 挺实用的 试试吧或许对您有用。(Imageprocess include recognized and others maybe good for you！)

这是一个介绍Matlab7.0的工具书，内容简单基础，适合初学者。(This is a presentation tool Matlab7.0 book, the content is simple foundation for beginners.)

Code is for extracting morphological, textural and statistical features cell image. Original image is diffused anisotropically and used for extraction of features leading to classifiction of cellular data

克里金法假定采样点之间的距离或方向可以反映可用于说明表面变化的空间相关性。克里金法工 具可将数学函数与指定数量的点或指定半径内的所有点进行拟合以确定每个位置的输出值。克里金法是一个多步过程；它包括数据的探索性统计分析、变异函数建模 和创建表面，还包括研究方差表面。当您了解数据中存在空间相关距离或方向偏差后，便会认为克里金法是最适合的方法。该方法通常用在土壤科学和地质中。(This function completes what I have started with the functions variogram and variogramfit. It is not intended to be a highly optimized code for performing kriging but may have educational value. Note that for using kriging, you should download the latest version of variogramfit. kriging uses ordinary kriging to interpolate a variable z measured at locations with the coordinates x and y at unsampled locations xi, yi. The function requires the variable vstruct that contains all necessary information on the variogram. vstruct is the forth output argument of the function variogramfit. This is a rudimentary, but easy to use function to perform an ordinary kriging interpolation. I call it rudimentary since it always includes ALL observations to estimate values at unsampled locations. This may not be necessary when sample locations are not within the autocorrelation range but would require something like a k nearest neighbor search algorithm or something similar. Thus, the alg)