a1128_2_No

The aim of the assignment is to understand the concept of the image enhancement stage We need to know the technique to improve the image or better input for the image processing technique as in the assignment. In the first part of the assignment is the segmentation using thresholding technique. Before we threshold the image, we need to prepare the better image for input such as histogram equalization to stretch the intensity value of the image before converting to binary image. In the second part of the assignment is about frequency domain. We need to transform the spatial image to frequency image using Fourier transform of the image before using the filter.

说明：  用matlab模拟圆孔衍射图像，入射光为平面波，衍射距离可以任意调节(Matlab simulation using circular aperture diffraction images, the incident light for the plane wave, diffraction can adjust the distance)

matlab线性拟合程序，和大家一起分享交流，一起学习(Matlab linear fitting procedures, and sharing together, learning together)

说明：  网络函数逼近实例1.首先定义正弦函数，采样率为20Hz，频率为1Hz 2.生成BP网络。用newff函数生成前向型BP网络，设定隐层中神经元数目为10 3.对生成的网络进行仿真并做图显示。 4.训练。对网络进行训练，设定训练误差目标为 1e-5，最大迭代次数为300 5.再次对生成的网络进行仿真并做图显示。(Network function approximation example)

最短路问题的D算法,供大家参考，谢谢，ps:j介绍要求的字好多(D-algorithm for the shortest path problem, for your reference, thank you, ps: j introduced the word required a lot of)

rotor reference frame model of induction motor

重要参数的提取，是本科毕设的题目，可以实现模式识别领域的数据的分类及回归，进行逐步线性回归，构成不同频率的调制信号，正确率可以达到98％，在MATLAB中求图像纹理特征。( Extract important parameters, The title of the commercial is undergraduate course you You can achieve data classification and regression pattern recognition, Stepwise linear regression, Constituting the modulated signals of different frequencies, Accuracy can reach 98 , In the MATLAB image texture feature.)

MFSK modulation is for underwater acoustic communication

segy数据格式读入，对地震资料处理有用，我开发的(segy read into the data format for seismic data processing useful, I developed)

基于Kumaresan和Tufts提出的music改进方法，以减小计算复杂度(Kumaresan and Tufts-based music made by improved method to reduce the computational complexity)