setup

雷达信号处理，巴克码信号波形仿真，主要是5位巴克码的仿真(Radar signal processing, Barker code waveform simulation)

实现产生伪随机序列的部件 —— 线性反馈移位寄存器单元。 SFlog2为扩频因子的底数为2的对数值，cycle为PN序列的周期，其值为2^SFlog2。initial_state为移位寄存器的初始状态，generator_polynomial_coefficient为生成PN序列所需的本原多项式，对应于移位寄存器的连接向量。(The realization of pseudo-random sequence generated components- LFSR unit. SFlog2 factor for the spread-spectrum base 2 of value, cycle for the PN sequence cycle, its value is 2 ^ SFlog2. initial_state shift register for the initial state, generator_polynomial_coefficient to generate the necessary PN sequence primitive polynomial, corresponding to the shift register connection vector.)

内点法对非凸非线性规划的解法，求得最优化的解。(Interior point method for solution of non-convex nonlinear programming, to achieve optimum solution.)

PHOTOVOLTAIC MODELISATION WITH SIMULINK

How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments. (How the K-mean Cluster workStep 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (Nk) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3. Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4. Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.)

基于时隙aloha的防碰撞改进算法,效率很高哦，希望对大家有用(ALOHA anti-conclusion alogrithm dddddd)

宽带模糊度函数程序，程序中包含了PCW、LFM、HFM和HFM+PCW四种信号，可以自行选择。(Wideband ambiguity function, the program contains four kind of signals, including PCW, LFM, HFM and HFM+PCW. Users can choose by yourself, or write the signals yourself.)

感知器算法是一种神经网络的模型，是20世纪50年代中期到60年代初人们对模拟人脑学习能力的一种分类学习机模型的称呼。当时的研究者认为它是一种学习的强有力模型，但以当时的技术无法实现非线性分类，许多实验室都放弃了感知器的研究。但其中的思想很经典，对后来的模式识别模型有很大的影响。当然，随着时代的进步，已经有很多学者提出了许多非线性的感知器改进算法，并取得良好效果，此程序主要基于Matlab来具体实现传统的感知器算法。(This program is based on Matlab to specifically achieve the traditional perceptron algorithm.)

本m文件讲了在matlab中如何生成一个EXCEL的文档模板，在以后做数据报表时可自动根据数据变化动态生成完整的动态的统计分析图表(This m file describes in matlab how to generate an EXCEL document template for the data reporting in the future when the data changes dynamically )

Advanced Engineering Mathematics With Matlab