solvemat

说明：  基于MATLAB的组合模型 在港口吞吐量预测中的应用 以某港1998--2007年集装箱吞吐量为实测数据，建立其集装箱吞吐量的灰色理论、三次指数平滑、三次多项式 等预测模型，在MATLAB下，对比该港集装箱吞吐量各模型预测拟合值与实际值的差异。分析了差异产生的原因及其单一预 测模型的局限性，提出了港口集装箱吞吐量组合预测法。其预测误差明显低于其它单模型。运用组合预测模型．可以降低误 差。提高预测精度。(A combination of MATLAB-based model in port throughput prediction of a Hong Kong 1998- 2007 container throughput for the measured data, the establishment of its container throughput of the gray theory, the three exponential smoothing, prediction models, such as cubic polynomial in MATLAB, the contrast of the Hong Kong container throughput of fitting the models to predict the value of the difference between the actual value. Analysis of the causes of differences and the limitations of a single prediction model, the combination of port container throughput prediction. Its prediction error was significantly lower than other single model. The use of combination forecasting model. Can reduce the error. Improve the prediction accuracy.)

FLC - RLS APPROACHES/ techniques

matlab code for ECG simulation using MATLAB

MPPT connected to Buck

FDM in for 3D Laplace problem

说明：  本程序用matlab生成白噪声，并且基于一个离散线性随机系统的模型生成了y(k)和x(k)，绘制出了x(k|k-1)和x(k)的对比曲线，求出了提前一步预报的误差协方差阵的稳定值(the procedures used Matlab generate white noise, and on a discrete linear stochastic systems model generated y (k) and x (k), mapping out the x (k | k-1) and x (k) contrast curves, get a step ahead forecasting error covariance matrix of stable value)

说明：  介绍了直接序列扩频通信的理论基础和模型, 并通过MATLAB 提供的Simulink 仿真平台对直扩通信系统进行了仿真(THE RESEARCH ON MODELING AND SIMULATION OF DIRECT-SEQUENCE SPREAD SPECTRUM COMMUNICATIONS SYSTEM BASED ON SOFTWARE RADIO.PDF)

小波变换进行图像压缩 采用matlab编程 (Wavelet transform for image compression Using matlab programming)

一种利用小波变换的水印算法，实现了盲检测，可以对抗常见的几何攻击。(a wavelet transform the watermark algorithm achieved a blind testing can be used to confront common geometric attacks.)

实现希尔伯特-黄变换的功能，并带有一段测试数据。希尔伯特-黄变换是使用EMD分解将信号分解为本征模态函数（IMF），然后求得IMF分量的瞬时频率。其对于非稳态和非线性信号具有优良的效果。(The function plot_hht is a realization of the Hilbert-Huang transform (HHT). The HHT decomposes a signal into intrinsic mode functions (or IMFs), and obtain the instantaneous frequency data. It is designed to work well for data that are nonstationary and nonlinear.)