chap03

钟型隶属函数-f参数变化钟型隶属函数-f参数变化(Bell-shaped membership function-f parameter bell-shaped membership function-f parameter)

在matlab的环境中，根据各种算法提取到的信息来输入SVM分类器中进行训练(classify different various sorts of information in svm)

小波去噪程序 在噪声环境下语音信号的增强 语音信号为读入的声音文件 噪声为正态随机噪声 (Wavelet denoising process voice signals in a noisy environment, the enhanced speech signal into a sound file for read noise is normal random noise)

SVM（支持向量机）参数寻优代码，可自动实现支持向量机的参数寻优(SVM (support vector machine) parameter optimization code that can automatically support vector machine parameter optimization)

利用matlab软件平台生成音乐音符，7个音符，不同的乐器实现(create a music tone)

亲测可用，完整版cca分析ssvep信号，可能没有数据，但是程序是好的(Pro test can be used, the full version of CCA analysis of SSVEP signals, there may be no data, but the program is good)

该程序用以对m序列码的调制在负dB情况下解调的仿真，是对基带信号的调制(procedures for the right sequence code m in the negative dB modulation of the demodulation simulation of the base band signal modulation)

说明：  In computer science, differential evolution (DE) is a method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. Such methods are commonly known as metaheuristics as they make few or no assumptions about the problem being optimized and can search very large spaces of candidate solutions. However, metaheuristics such as DE do not guarantee an optimal solution is ever found.

说明：  数字图像修复算法的评价标准也是从两个方面进行评价的，一个是修 复算法的效率，一个是修复后图像质量。修复算法的效率主要就是看修复 图像所用的时间，可以用时间就行量化。而图像质量很难从量上唯一的进 行评价，目前图像修复质量还没有统一的评价标准，从实际应用出发，修 复后图像质量的好坏大多数是从以下两个方面就行评价，修复后图像给人 主观上的“满意度”和客观上图像的cnr、enl、epi、psnr、snr来评判。(The evaluation criteria of digital image restoration algorithms are also evaluated from two aspects, one is repair. One of the efficiency of complex algorithm is the image quality after restoration. The efficiency of the repair algorithm depends mainly on the repair. The time spent on the image can be quantified in terms of time. But image quality is difficult to improve quantitatively only. At present, there is no uniform evaluation criterion for image restoration quality. Starting from practical application, repair The quality of restored images is mostly evaluated from the following two aspects, and the restored images are given to people. Subjective "satisfaction" and objective image cnr, enl, epi, psnr, SNR to judge.)

Fibonacci m file in matlab