stft

往年研究生数学建模的题目以及获奖论文，包含很多例子。(Usual mathematical model, the title of the paper, and contains a lot of examples. )

manipulate and solve systems of multivariate polynomial equations by computing the groebner basis

Mean Shift 这个概念最早是由Fukunaga等人[1]于1975年在一篇关于概率密度梯度函数的估计中提出来的,其最初含义正如其名,就是偏移的均值向量,在这里Mean Shift是一个名词,它指代的是一个向量,但随着Mean Shift理论的发展,Mean Shift的含义也发生了变化,如果我们说Mean Shift算法,一般是指一个迭代的步骤,即先算出当前点的偏移均值,移动该点到其偏移均值,然后以此为新的起始点,继续移动,直到满足一定的条件结束. 用matlab实现mean shift算法仿真(Mean Shift the concept was first used by Fukunaga et al [1] in 1975 in an article on the probability density function estimation of gradient raised its original meaning, as its name implies, is the offset of the mean vector, where is the Mean Shift a noun, it refers to a vector, but with the Mean Shift the development of the theory, Mean Shift the meaning has changed, if we say that Mean Shift algorithm, generally refers to an iterative steps, namely, first calculate the current point Mean offset, move the shift points to its average, and then as a new starting point and continue to move until the end to meet certain conditions. realize using mean shift algorithm matlab simulation)

this is the code to illustrate greedy algorithm in matlab

A. Fusion at the Feature Extraction Level The data obtained from each sensor is used to compute a feature vector. As the features extracted from one biometric trait are independent of those extracted from the other, it is reasonable to concatenate the two vectors into a single new vector. The primary benefit of feature level fusion is the detection of correlated feature values generated by different feature extraction algorithms and, in the process, identifying a salient set of features that can improve recognition accuracy [14]. The new vector has a higher dimension and represents the identity of the person in a different hyperspace. Eliciting this feature set typically requires the use of dimensionality reduction/selection methods and, therefore, feature level fusion assumes the availability of a large number of training data.

说明：  MIMO通信系统中两点结构模型下采用ZF准则预编码检测误码率性能的仿真(MIMO communication systems in the two structural model under the rule of using ZF precoding detection bit error rate performance of the simulation )

说明：  基于相位一致的边缘检测算法，matlab源代码(Based on the same edge detection algorithm phase, matlab source code)

说明：  Matlab codes for adaptive antennas

说明：  数字图像处理(实验二) 图像的读、写、显示和点运算 1、掌握函数imadjust与对数和对比度拉伸变换； 2、掌握直方图的绘制和直方图均衡化变换； 3、掌握空间滤波。 (Digital image processing (Experiment 2). the image to read, write, display and point operations a master function imadjust with the number and contrast stretching transformation 2, control histogram drawing and the histogram equalization transformation 3, master spatial filtering .)

用MATLAB实现对图形图像的处理，图像的平滑滤波。(Realized by MATLAB graphics image processing, image smoothing.)