模拟退火算法

整数小波变换与图像压缩 用MatLAB实现图像的整数小波变换，对行和列各做一次。采用最简单的S小波，它是Haar变换的整数形式。(integral wavelet transform and image compression .To realize the integral wavelet transform based on the Matlab in rows and columns. Using the simple S wavelet ,which is integral form of the Haar transform)

A GUI for browsing and finding region of interent in a gaussion noise filtered image.

用于现代信号分析与处理课程，作用是实现K-L变换和DCT变换。(For modern signal analysis and processing programs, the role is to achieve the KL transform and DCT.)

srukf 代码，经试验可用，可以解决ukf在模型不匹配时出现的发散或者不稳定等问题(srukf code, used by the pilot, can solve ukf model mismatch occurs when the divergence or instability problems)

说明：  基于Cao方法求得混沌时间序列相空间重构的最优化嵌入维的Matlab程序(Cao method, based on the chaotic time series reconstruction phase space optimization of the embedded peacekeeping procedures Matlab)

基于PCA法的人脸识别，对本科毕业设计具有参考价值(含源代码和实验图片)(based PCA Face Recognition Act, the undergraduate graduation design reference value (including source code and experimental Photo))

说明：  seir模型模拟传染病 人在康复以后产生了抗体就不会再得病。不同于SIS模型，我们在模型中引入康复者(The Recovered)，用 [公式] 表示，并满足总人数 [公式] 。这个时候就是SIR模型。一旦变为康复者，就不会再传染，即在概率传递过程中，一旦变为康复者，就没有概率再次转移为感染者或者易感者。我们假设感染者变为康复者的概率为我们来看下SIR模型的微分方程(SEIR model simulating infectious diseases)

说明：  为了提升配网供电可靠性的预测精度!提出了基于主成分分析和粒子群优化极限学习机的配网供电可靠 性预测模型$ 从多方面分析影响供电可靠性的指标!利用主成分分析得到综合变量!实现对数据的降维$ 在此基 础上!构建人工神经网络并利用粒子群算法优化极限学习机的输入权值和阈值!完成对训练供电可靠性预测模型 的训练$ 以某大型电网的 ?L 个供电局样本 !% 种影响供电可靠性因素为例进行仿真分析!并将 E S R C E FQ C 4 G D算 法与 ! 种回归拟合算法对比!验证了该方法的有效性(It is clear that the learning speed of feedforward neural networks is in general far slower than required and it has been a major bottleneck in their applications for past decades. Two key reasons behind may be: (1) the slow gradient-based learning algorithms are extensively used to train neural networks, and (2) all the parameters of the networks are tuned iteratively by using such learning algorithms. Unlike these conventional implementations, this paper proposes a new learning algorithm called extreme learning machine (ELM) for single-hidden layer feedforward neural networks (SLFNs) which randomly chooses hidden nodes and analytically determines the output weights of SLFNs. In theory, this algorithm tends to provide good generalization performance at extremely fast learning speed. The experimental results based on a few artificial and real benchmark function approximation and classification problems including very large complex applications show that the new algorithm can p)

matlab图像处理 图像处理常用函数集锦 总结出来大家分享一下(matlab image processing function image processing used to share with you highlights summed up)

脑波FFT变换 调用格式见m文件头部说明（下边也复制了一份） 有配套.DLL.h.lib.ctf文件，可以在C或C++环境中调用 ------------------------------------ 保存为FFT.m文件 输入参数： N：进行FFT变换的点数（要求是2的N次幂）； fs：信号的采样频率（frequency of simpling） sig：进行FFT变换的数组（一维）。 输出参数： f_sig:变换后的信号（一维数组） E_delta、E_theta 、E_alpha、E_beta分别表示δθαβ相应频段的能量加和。 other为其余频段的能量加和（供参考用） -------------------------------------------------------------------------- function[ f_sig ,E_delta , E_theta , E_alpha , E_beta , other ] = FFT( N , fs , sig )(EEG FFT transform is called m file format, see head illustrate the matching DLL files, you can be C or C++ to call------------------------ simpling) sig: to FFT transform array (one dimension). Output Parameters: f_sig: transformation of the signal (one-dimensional array) E_delta, E_theta, E_alpha, E_beta δθαβ, respectively, the energy increases and the corresponding frequency band. Other for the rest of the energy band increases, and (for reference) -------------------------------------------------------------------------- function [f_sig, E_delta, E_theta, E_alpha, E_beta , other] = FFT (N, fs, sig))