XiaoSpectra30M

学习的一个产物，供大家作为实验的参考，不好的地方见谅(A product of learning for us as a reference experiment, where poor excuse me)

采用贝叶斯正则化算法提高 BP 网络的推广能力。 在本例中，我们采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络，使其能够拟合某一附加有白噪声的正弦样本数据。(Bayesian regularization algorithm to improve the generalization ability of BP network. In this example, we use two training methods, namely LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr), to train BP network so that it can fit a sine additional white noise sample data.)

用matlab实现神经网络的城市交通流量预测。主要以大脑生理变化过程为基础、模仿大脑的结构和功能(Neural network using matlab implementation of the urban traffic flow prediction. Major physiological changes to brain-based process, to imitate the structure and function of the brain)

quisi z_source inverters

给出卫星适当的初始位置和速度，利用其运动微分方程，求卫星运行的轨道（航天航空）( Appropriate given the initial satellite position and velocity, using the equations of motion, find the satellite orbit)

非线性调频信号产生程序，根据给定的窗函数综合出相应的NLFM信号(Non-linear FM signal generation process, according to the given window function the corresponding NLFM signal integrated)

基于FFT的图像匹配，用傅立叶变换对图像进行匹配！分别对模板和匹配图进行傅立叶变换(image Regsiter use FFT )

现代通信系统中广泛应用的GMSK调制与解调方式仿真模拟 多图 有很强的说明性 呕心沥血啊(In modern communications systems widely used in GMSK modulation and demodulation method simulation of multi-map has a strong descriptive heart out ah)

根据接收数据阵x 、信道长度LH、过采样因子q ，采用Hopfield 盲处理方法，恢复出相应于x的尽可能长的BPSK发送序列，并估计 信道。(Based on the received data matrix x, the channel length of the LH, oversampling factor q, with Hopfield blind treatment, recovery corresponding to x, send a sequence of BPSK as long as possible, and the channel estimate.)

PCA and PLS aims:to get some insight into the bilinear factor models Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression, focusing on the mathematics and numerical aspects rather than how s and why s of data analysis practice. For the latter part it is assumed (but not absolutely necessary) that the reader is already familiar with these methods. It also assumes you have had some preliminary experience with linear/matrix algebra.