NOMA

回声状态神经网络(ESN)是一种性能优异的递归神经网络，已经在各领域广泛研究，这是ESN的发明人研制的MATLAB工具箱，可供有关人员参考使用(Echo state neural networks (ESN) is a performance of recurrent neural networks have been extensively studied in various fields, which is ESN inventor developed MATLAB toolbox, use and reference available to the persons)

Matlab教程第7章，编程与数据分析、整理(Matlab Guide Chapter 7, programming and data analysis, sorting)

matlab多目标跟踪的源码 有各种滤波方法好 数据关联方法(matlab MMT)

用于混沌时间序列自适应预测的一种稀疏Volterra滤波器-(Adaptive prediction of chaotic time series for a sparse Volterra filter-)

说明：  利用粒子群算法求最小值，对基本粒子群做了修改，使其有更好的计算效果。(Using Particle Swarm Optimization for the minimum of basic particle swarm made changes to make it a better calculation of results.)

research paper for m.tech students

PLC MZI MATLAB仿真. MZI可用作波分复用器件（分离两个波长光信号）。本例子为一级MZI，由两个光耦合器（耦合系数a1,a2）和一段延迟臂（延迟dl）构成。MZI有两个输入和两个输出端口，一般两个波长光信号由一个输入端口输入，而在两个端口分别输出不同波长信号。(PLC MZI simulation.)

an introduction to dynamic meterology chapter 5-9 chapter matlab所有代码 气象专业经典资料(an introduction to dynamic meterology chapter 5-9 matlab code)

鉴于本人去年7月份发布的《关于粗糙集和邻域粗糙集的基本理论和程序算例》其中有一些错误，可能给相关研究人员带来了误解，在此向大家道歉！ 同时在此资源中新增加了本人编写的邻域粗糙集的matlab计算程序，包括正域计算，约简计算，重要度计算，权重计算。 欢迎大家下载并交流学习！ 我所发布的两个版本的说明，以第二版本为主，第一个版本就不要下载了。 版权所有，除百度文库和中国程序员联合开发网上能下载到相关资源外，其他网站上的均为盗用。请尊重知识产权！(Given that I released last July, " the basic theory and procedures for rough sets and neighborhood rough set of examples," of which there are some errors, researchers may be brought to the relevant misunderstanding here to apologize! While a new addition to this resource I prepared matlab calculation procedures neighborhood rough set, including the positive domain calculation, reduction calculation, it is important calculation, the weight calculation. Welcome to download and share their knowledge! Two versions of the instructions I have released the second version of the main, the first version, do not download. Copyright, except Baidu library and Chinese programmers can be downloaded to the joint development of Internet-related resources, are stolen on other sites. Please respect the intellectual property rights!)

第一步是计算输人信号单边功率谱密度（ESD）。使用快 ％速傅里叶（FFr）算法将信号从时域转换到频域。因为FFr算法的输出是离散谱，而这 ％里我们需要的是连续谱，因此需要引人不同的比例因子来实现从离散谱到连续谱的转换。 ％在第二步中，我们利用迭代算法计算出相对于特定阂值的ESD的最高和最低频率，从而 ％估算出被检测信号所占用的带宽。这种算法同时适用于基带信号和已调制信号。最后， ％在第三步中，我们给出了输出图形的原代码。(The first step is calculating the input signal unilateral power spectral density (ESD). The use of fast Fourier speed (FFr) algorithm for the signal conversion from time domain to frequency domain. FFR algorithm because the output is a discrete spectrum, which we need is a continuous spectrum, so the need for food of different scale factor to achieve from the discrete spectrum to continuous spectrum conversion. In the second step, we use iterative algorithm to calculate a specific threshold in relation to the ESD of the highest and lowest frequency, thus estimated to be occupied by the signal detection bandwidth. This algorithm applies to both baseband signal and modulation signals. Finally, in the third step, we give the graphical output of the original code.)