shoushishibie

基于matlab的程序讲解，综合了所有知识及仿真，希望能帮助你学习(Combines all the knowledge and simulation matlab-based program to explain, hope to help you learn)

spectrum sensing is used for communication purpose. Matlab code is utilized for detecting signal by using energy detection noise.

设计一维纳滤波器 (1)产生三组观测数据：首先根据s(n)=a s(n-1)+w(n)产生信号s(n)，将其加噪（信噪比分别为20dB,10 dB，6 dB），得到观测数据x1(n), x2(n), x31(n). (2)估计xi(n)，i=1,2,3的AR模型参数。假设信号长度为L，AR模型阶数为N，分析实验结果，并讨论改变L,N对实验结果的影响。 (A Wiener filter design (1) to produce three sets of observations: first generating a signal s (n) according to s (n) = as (n-1)+w (n), to add noise (20dB SNR, respectively , 10 dB, 6 dB), to obtain observational data x1 (n), x2 (n), x31 (n). (2) estimate xi (n), i = AR model parameters 1,2,3. Assuming the signal length L, AR model of order N, analysis of experimental results and discuss the impact changing L, N of the experimental results.)

tent帐篷映射分岔图 Henon映射 matlab 运行可直接看图(tent map, bifurcation graphs for a tent and henon system)

说明：  风光混合储能的生命周期费用考虑包括蓄电池、超级电容器的生命周期费用，(Life cycle cost considerations for landscape hybrid energy storage include life cycle costs for batteries and supercapacitors.)

蚁群算法的matlab源码,写在word里，请大家分享。(Ant colony algorithm matlab source code, written on the word, please share with you all.)

说明：  使用matlab对图像进行特征提取的例子。对图像中的车牌号进行读取。(Use the image feature extraction matlab example. License plate number on the image to read.)

matlab 用于数值积分，运用辛普森法(matlab for numerical integration, using Simpson' s method)

Algorithm Given are P training pairs {X1,d1,X2,d2....Xp,dp}, where Xi is (n*1) di is (n*1) No of Categories=R. i=1,2,...P Yi= Augmented input pattern( obtained by appending 1 to the input vector) i=1,2,…P In the following, k denotes the training step and p denotes the step counter within the training cycle Step 1: c>0 , Emin is chosen, Step 2: Weights are initialized at w at small values, w is (n+1)*1. Counters and error are initialized. k=1,p=1,E=0 Step 3: The training cycle begins here. Input is presented and output computed: Y=Yp, d=dp Oi=f(wtY) for i=1,2,….R Step 4: Weights are updated: wi=wi+1/2c(di-oi)Y for i=1,2,…..R. Step 5: Cycle error is computed: E=1/2(di-oi)2+E for i=1,2,…..R. Step 6: If p<P then p=p+1,k=k+1, and go to Step 3: Otherwise go to Step 7. Step 7: The training cycle is completed. For E=0,terminate the training session. Outputs weights and k. If E>0,then E=0 ,p=1, and enter the new training cycle by going to step 3.

8 kW DC DC BOOST to connect source of energy