fdtd近场仿真的matlab源代码

说明：  国外人写的LTE链路级仿真文件，对于初学LTE的人有很大的帮助(Written by foreign LTE Link Simulation file, LTE for the beginner who is very helpful)

column to row source code

正交频分复用是一种多载波宽带数字调制技术。相比一般的数字通信系统， 它具有频带利用率高和抗多径干扰能力强等优点，因而适合于高速率的无线通信系统。( OFDM Simulator -------------------------------------------------------------------------------- MIMO OFDM Simulator: OFDM.m: OFDM Simulator (outer function) create_channel.m: Generates a Rayleigh fading frequency-selective channel, parametrized by the antenna configuration, the OFDM configuration, and the power-delay profile. svd_decompose_channel.m: Since full channel knowledge is assumed, transmission is across parallel singular value modes. This function decomposes the channel into these modes. BitLoad.m: Apply the bit-loading algorithm to achieve the desired bit and energy allocation for the current channel instance. ComputeSNR.m: Given the subcarrier gains, this simple function generates the SNR values of each channel (each singular value on each tone is a separate channel). chow_algo.m: Apply Chow s algorithm to generate a particular bit and energy allocation. EnergyTableInit.m: Given the SNR values, form a table of energy increments for )

OFDM系统的自适应功率和比特分配算法，实现系统资源的自适应分配（4)－－原创(adaptive allocation for OFDM system)

有相位跳变的单频信号，信号时域波形的刻画和FFT程序。注释完整，可读性高。(a single-frequency signal with phase jump and its FFT is described in this program and the explain is detailed, easy to read.)

说明：  珍藏版，可实现，新K均值聚类算法，分为如下几个步骤： 一、初始化聚类中心 1、根据具体问题，凭经验从样本集中选出C个比较合适的样本作为初始聚类中心。 2、用前C个样本作为初始聚类中心。 3、将全部样本随机地分成C类，计算每类的样本均值，将样本均值作为初始聚类中心。 二、初始聚类 1、按就近原则将样本归入各聚类中心所代表的类中。 2、取一样本，将其归入与其最近的聚类中心的那一类中，重新计算样本均值，更新聚类中心。然后取下一样本，重复操作，直至所有样本归入相应类中。 三、判断聚类是否合理 采用误差平方和准则函数判断聚类是否合理，不合理则修改分类。循环进行判断、修改直至达到算法终止条件。(NewK-means clustering algorithm ，Divided into the following several steps: A, initialize clustering center 1, according to the specific problems, from samples with experience selected C a more appropriate focus the sample as the initial clustering center. 2, with former C a sample as the initial clustering center. 3, will all samples randomly divided into C, calculate the sample mean, each the sample mean as the initial clustering center. Second, initial clustering 1, according to the sample into the nearest principle clustering center represents the class. 2, as this, take the its recent as clustering center of that category, recount the sample mean, update clustering center. And then taking off, as this, repeated operation until all samples into the corresponding class. Three, judge clustering is reasonable Adopt error squares principles function cluster analysis.after clustering whether reasonable, no reasonable criterion revisio)

MATLAB MEANSHIFT 图像 处理 代码(The MATLAB MEANSHIFT image processing code)

自适应和灰色模型的一些相应代码，根据论文写的，和结果一样。(Some adaptive code and corresponding gray model, according to a paper written and the same results.)

该MATLAB程序实现了simplex迭代算法，该算法可以在不对目标函数求导情况下进行优化，适合数据量较大的算法优化。(The MATLAB program to achieve a simplex iterative algorithm, which can be optimized in the right objective function derivation, the large amount of data suitable algorithm optimization.)