adapteq_graphics

matlab与vc混合编排的问题，可以得到有效解决，详细介绍后还有编码实现哦(Matlab and vc mixed scheduling issues can be effectively resolved After detailed There Coding oh)

蚁群算法实现连续极值求解，一般是二维函数的求解(solve the biggest value of function)

MATLAB资料是学习MATLAB的最好帮手(MATLAB data is the best helper to learn MATLAB)

程序代码说明 P0301：数字图像矩阵数据的显示及其傅立叶变换 P0302：二维离散余弦变换的图像压缩 P0303：采用灰度变换的方法增强图像的对比度 P0304：直方图均匀化 P0305：模拟图像受高斯白噪声和椒盐噪声的影响 P0306：采用二维中值滤波函数medfilt2对受椒盐噪声干扰的图像滤波 P0307：采用MATLAB中的函数filter2对受噪声干扰的图像进行均值滤波 P0308：图像的自适应魏纳滤波 P0309：运用5种不同的梯度增强法进行图像锐化 P0310：图像的高通滤波和掩模处理 P0311：利用巴特沃斯（Butterworth）低通滤波器对受噪声干扰的图像进行平滑处理 P0312：利用巴特沃斯（Butterworth）高通滤波器对图像进行锐化处理(Code Description P0301: digital image data display matrix and Fourier transform P0302: Two-dimensional discrete cosine transform image compression P0303: gray-scale transformation method using the contrast enhanced image P0304: Histogram of homogenization P0305: simulated images by Gaussian white noise and salt and pepper noise of P0306: two-dimensional median filter function medfilt2 on the image noise by filtering salt and pepper P0307: using MATLAB in the function filter2 noise on the image by mean filter P0308: Image Adaptive Weiner Filter P0309: the use of 5 different gradient enhanced image sharpening method P0310: the image of the high-pass filter and mask treatment P0311: Using Butterworth (Butterworth) low pass filter the image noise by smoothing P0312: Using Butterworth (Butterworth) high pass filter sharpening the image)

to detect the energy in cognitive radio

Aiming at determining the satellite attitude precisely，the gyros bias and m isa lignment were compensated in time by using the quaternion of star-sensor and extended Kalm an filter．The related module of the filter was derived．The theoretic accuracy of the algorithm was acquired from the numerical simulation． The effects of the star-senso r misalignment on attitude determination were analyzed at last．

不同光程比值对色散关系的影响，光子晶体中光程的比值定义为高低折射率所对应的光程的比值，计算公式为定义为 (Effects of different length ratio on the dispersion relation)

说明：  实验一：基于LMS算法的“苹果-橘子”分类问题 实验二：基于LMS算法的T-G-F字符识别问题 通过以上两个实验，了解ADALINE网络的结构及计算机制，掌握LMS算法，并会利用该算法来解决简单的模式分类问题。1， 学习ADALINE网络的基本结构及其学习机制，并在Matlab中实现 2， 分别对上述两类分类问题进行实现，并根据实验结果完成实验报告 (Experiment 1: Based on LMS Algorithm Apple- Orange classification issues Experiment two: TGF-based character recognition problem LMS algorithm Through the above two experiments to understand the structure and computer network system ADALINE, master LMS algorithm, and will use the algorithms to solve simple pattern classification problem. 1, learn the basic structure and learning mechanism ADALINE network and to achieve in Matlab 2, respectively, for these two types of classification problems were implemented and completed in accordance with the experimental results of test report)

本文主要是JTIDS的传输性能做了仔细的评估，并对其抗干扰做了一一的介绍。(The Joint Tactical Information Distribution System (JTIDS) provides jam-resistant digital communication of data and voice for command and control, relative positioning and identification. Many advanced technologies are adopted in JTIDS, such as frequency hopping, M-ary spread spectrum, error detection and correction.)

create menu in matlab graph sin cos