MoM

通信系统systemview的系统仿真与设计,北航版(systemview)

optimal extreme machine learning

利用matlab计算切趾布拉格光栅的反射谱(calculating the reflection spectra of apodized Bragg fiber grating )

50欧姆,100欧姆板厚1.0MM8层板阻抗设计-金百泽阻抗控制结构确认函(1mm8layout100ohm50ohm Impedance matching )

设模拟带通信号频率范围1KHz—1.1KHz，设计一个采样频率8KHz数字频谱分析系统，要求频率分辨率0.1Hz。若对信号直接用FFT进行频谱分析(simulation based communications, with the frequency range 1KHz- 1.1KHz. Design of an 8 KHz sampling frequency digital spectrum analysis system requirements frequency resolution 0.1 Hz. If the signal directly FFT spectrum analysis)

说明：  带时间滞后项的最小二乘法，主要用于金融时间序列数据的拟合(least square method)

三维FDTD程序，计算了一细直半波振子的方向图和方向性系数，考虑了细天线的处理方法。(Three-dimensional FDTD program to calculate a fine straight half-wave dipole pattern and directivity, consider the approach of fine antenna.)

运用matlab模拟各种随机变量，内容包括模拟的基本思路和matlab代码(Use matlab simulate various random variables, including the basic ideas and matlab simulation code)

DFT变换求相位差和振幅大小程序，可以滤除噪声精确求得相位差和幅度值(DFT code)

极限学习机（extreme learning machine）ELM是一种简单易用、有效的单隐层前馈神经网络SLFNs学习算法。2006年由南洋理工大学黄广斌副教授提出。传统的神经网络学习算法（如BP算法）需要人为设置大量的网络训练参数，并且很容易产生局部最优解。极限学习机只需要设置网络的隐层节点个数，在算法执行过程中不需要调整网络的输入权值以及隐元的偏置，并且产生唯一的最优解，因此具有学习速度快且泛化性能好的优点。(Extreme Learning Machine (extreme learning machine) ELM is an easy-to-use and effective single hidden layer feedforward neural network the SLFNs learning algorithm. 2006 by the Nanyang Technological University Associate Professor Huang Guangbin. Traditional neural network learning algorithm (BP) artificial network training parameters, and it is easy to generate a local optimal solution. Extreme Learning Machine network only need to set the number of hidden nodes, the algorithm implementation process does not need to adjust the network input weights and hidden element of bias, and only optimal solution, so the learning speed and generalization good performance advantages.)