peak-finding

matlab揭秘的附件， 带图带源码文件，456章(the matlab Secret Annex, band diagram with source code files, 456)

说明：  关于超宽带（UWB）一些信道的matlab仿真程序。(On ultra-wideband (UWB) channel matlab simulation of some procedures.)

说明：  单端口网络函数施加阶数缩减方法，并附详细题解(Single-port network functions to impose order reduction method, together with a detailed solution question)

说明：  为了提高认知无线电中感知用户对授权用户(主用户) 的检测概率,提出一种新的基于循环 谱统计量的主用户信号检测算法. 该算法利用循环谱离散频域平滑方法,对信号的循环谱在循环频 率处建立合理的检测统计量,然后求解得到对应不同虚警概率的判决门限,以使感知用户能检测信 噪比更低的授权用户信号.(To increase the detection probability of sensing users for licenced users (primary signals) in the cognitive radio , it put s forward a new primary users signal method based on cyclic spect rum statis2 tics. By using discrete f requency smoothing of cyclic spect rum , this algorithm establishes the reason2 able detection statistics on the cyclic f requency of signal cyclic spect rum , then solves and obtains the decision threshold correspond to different false alarm probability , as a result , making the sensing users can detect licenced users signal under lower signal in noise ratio (SNR) .)

LMS算法的MATLAB实现函数, 输入参数: xn 输入的信号序列 (列向量) dn 所期望的响应序列 (列向量) M 滤波器的阶数 (标量) mu 收敛因子(步长) (标量) 要求大于0,小于xn的相关矩阵最大特征值的倒数 itr 迭代次数 (标量)(LMS algorithm MATLAB realization function)

Book of Neural Network Toolbox For Use with MATLAB®

利用Matlab编写构造最小生成树的Prim算法，程序注释清晰，通俗易懂。(Minimal Spanning Tree-- Prim)

压缩文件中有两个文件，其中一个是基于BP、RBF人工神经网络解决变压器故障诊断的问题。另外一个文件是用进退法、黄金分割法、DFP、Powell的方法解决函数最小值。( There are two archive files, one of which is based BP, RBF artificial neural network to solve the problem of transformer fault diagnosis. Another document is the solution to function with the minimum of advance and retreat method, golden section method, DFP, Powell method.)

说明：  可以通过截取文献中的图片进而提取文献曲线中的数据(capture the data of curves in ref.)

这里的DDS(直接数字合成)是我在MATLAB中用Simulink基本模块搭建起来的模型,仿真DDS信号的产生,并有一个M文件实现与模型同等的功能,MATLAB爱好者一定不要错过(I build the DDS model using simulink basic model to simulate the DDS source, associated a M file realizing the same function as the model,and,the MATLAB lovers must not miss)