pca

matlab基础中课后习题，一个非常简单的MATLAB小程序，用二分法求根(matlab based after-school exercise in a very simple little program MATLAB, with the dichotomy Roots)

Direct Sequence Spread Spectrum

（压缩包里一共有5个代码） pca+lda+粗糙集+模糊神经网络 saveORLimage.m将ORL人脸库分为测试集ptest和训练集pstudy存为imagedata.mat 1.savelda.m将人脸库先进行pca降维，再用lda进行特征提取，得到新的测试集ldatest和训练集ldastudy存为imageldadata.mat 2.对ldastudy进行离散化(discretimage.m)，得到离散化矩阵disdata,存入到imagedisdata.mat 3.将disdata组成决策表(savers.m)，通过对disdata的条件属性进行约简，得到其一个约简，组成新的测试集rstest和训练集rsstudy存为imagersdata.mat 4.对rsstudy进行模糊神经网络训练(savecul.m)，对模糊神经网络的参数进行调整学习将其存入culdata.mat 5.用runfnn.m对rstest进行测试得到其识别率 savem.m和cm.m是用最小距离分类器对训练集和测试集进行分类.(pca+ lda+ Rough Set+ fuzzy neural network saveORLimage.m will ORL face database is divided into test set and training set ptest for pstudy keep imagedata.mat Treasury will face 1.savelda.m first dimensionality reduction pca, lda used feature extraction, a new test set and training set ldatest for ldastudy keep imageldadata.mat 2. Ldastudy carried out on the discretization (discretimage.m), to be discrete matrix of disdata, deposited to imagedisdata.mat 3. Disdata the composition of the decision table (savers.m), the conditions on the attributes disdata about Jane, has been one of its reduction to form the new test set and training set rstest for rsstudy keep imagersdata.mat 4. Rsstudy training fuzzy neural network (savecul.m), on the parameters of fuzzy neural network to learn to adjust their deposit culdata.mat 5. Rstest used to test for runfnn.m by its recognition rate cm.m is savem.m and minimum distance classifier on the training set and test set classificati)

人脸识别算法实现 (Face Recognition Algorithm )

music 算法解决问题续,欠估计情况下的精度(music algorithm to solve the problem continued, underdevelopment of the estimated accuracy)

自己编写的AR过程信号线形预测器RLS算法。(I have written of the AR process of linear prediction RLS algorithm)

局部均值分解是由Smith提出的一种新的非线性和非平稳信号分析方法。由于LMD是依据信号本身的信息进行自适应分解的，产生的PF分量具有真实的物理意义，由此得到的时频分布能够清晰准确地反映出信号能量在空间各尺度上的分布规律。(Local mean decomposition is a new nonlinear and non-stationary signal analysis method proposed by the Smith. Since LMD information is based adaptive signal itself decomposed, resulting PF component has real physical meaning, when the resultant frequency distribution of the signal can be clearly and accurately reflect the spatial distribution of the energy of each scale.)

粒子束算法 matlab 站长把时间都花(pos matlab calculator 容说明(至少要20个字)。尽量不要让站长把时间都花费在为您修正说)

说明：  近年来，基于启发式的多目标优化技术得到了很大的发展，研究表明该技术比经典方法更实用和高效。有代表性的多目标优化算法主要有NSGA、NSGA-II、SPEA、SPEA2、PAES和PESA等。粒子群优化(PSO)算法是一种模拟社会行为的、基于群体智能的进化技术，以其独特的搜索机理、出色的收敛性能、方便的计算机实现，在工程优化领域得到了广泛的应用，多目标PSO(MOPSO)算法应用到了不同的优化领域[9~11]，但存在计算复杂度高、通用性低、收敛性不好等缺点。 多目标粒子群（MOPSO）算法是由CarlosA. Coello Coello等在2004年提出来的(In recent years, heuristic-based multi-objective optimization technology has been greatly developed, and research shows that this technology is more practical and efficient than classical methods. Representative multi-objective optimization algorithms mainly include NSGA, NSGA-II, SPEA, SPEA2, PAES and PESA. Particle Swarm Optimization (PSO) algorithm is an evolutionary technology based on swarm intelligence that simulates social behavior. With its unique search mechanism, excellent convergence performance, and convenient computer implementation, it has been widely used in the field of engineering optimization. The objective PSO (MOPSO) algorithm is applied to different optimization fields [9~11], but it has shortcomings such as high computational complexity, low versatility, and poor convergence. The multi-objective particle swarm optimization (MOPSO) algorithm was proposed by Carlos A. Coello Coello et al. in 2004)

说明：  数据通道剥离伪码后的载频估计,数据通道剥离伪码后的载波估计问题。对直接序列扩频系统的数据通道，假定接收设备已“完美”地锁定接收信号伪码，并实现了伪码剥离其中，信号幅度、电文、载波多普勒和载波相位均未知。电文的速率为10Hz。由于信源与接收端信号传输时延的不确定性，收到的信号电文是从某个未知时刻开始的。 利用数据文件 估计信号幅度、载波多普勒和载波相位(Data channel after stripping pseudo-code carrier frequency estimation)