textbook-of-MATLAB

The channel modeling work package WP1 of IST-WINNER project provided a Matlab implementation of the WINNER Phase II Model (referred as WIM this onward). The main purpose of the WIM channel models is to generate a radio channel realisations for a link and system level simulations. The implementation is based on the earlier implementations of WINNER II interim model [6], WINNER I (interim) model [3], 3GPP/3GPP2 Spatial Channel Model (SCM) [4] and SCM(E) Extension models. For details concerning the WIM model, please refer to [1]. This document describes the SW implementation structure of WIM, its input/output interface and its functionality. Channel model scenarios and parameters are modified to correspond to IMT.EVAL [7] channel model.

matlab project chapter 001

通过此代码实现萤火虫算法仿真，改变函数，即可实现不同的函数结果。(This code implements the firefly algorithm simulation, change the function, you can achieve different function results.)

产生SVD,GMD预编码程序 ,能产生对比图，是很好的仿真程序(acomplish the SVD and GMD procoing)

The local binary pattern (LBP) is a simple yet very efficient operator which labels the pixels of an image by thresholding the neighborhood of each pixel and considers the result as a binary number. Perhaps the most important property of the LBP operator in real-world applications is its invariance against monotonic gray level changes caused, for example, by illumination variations. Another equally important is its computational simplicity, which makes it possible to analyze images in challenging real-time settings. LBP is also very flexible: it can be easily adapted to different types of problems and used together with other image descriptors

欧洲中心ERA-interim再分析资料处理(ECMWF ERA-interim reanalyse data )

说明：  改程序实现了模糊控制与模糊神经网络的等价转换！欢迎下载！(Reform program to achieve a fuzzy control and fuzzy neural network is equivalent to conversion! Welcome to download!)

similarity measurement ,to get the eigenvalue

The state space model is nonlinear and is input to the function along with the current measurement. The function performs the extended Kalman filter update and returns the estimated next state and error covariance

说明：  读取图像lena.tif，进行DCT变换，每个图像块保留10个DCT系数进行重构图像，比较重建图像与原始图像的差异。(Read the image lena.tif, the DCT transform, each image block of 10 DCT coefficients to retain the reconstructed image, reconstructed image compared with the original image differences.)