U_PCM

该程序完成了一个DPSK通信系统的仿真，用均匀随机数发生器产生01比特对，用差分编码将每2比特符号映射到4种信号点中之一个，绘制出了DPSK的误码率。( This procedure has completed a DPSK communications system s simulation, produces 01 bit right with the even random number generator, maps with the differential coding every 2 bits marks to of 4 kind of signal locations, drew up the DPSK error rate. )

Vc++下如何利用Matlab工具箱进行数字信号处理(Vc++ how to use Matlab toolbox for digital signal processing)

floyd算法的matlab实现，最短路问题的一种解法(floyd algorithm of the Matlab implementation, the shortest path to a solution of the problem)

说明：  matlab编程引擎(matlab programming engine)

用于决策树中对数据进行分类，适合机器学习等领域(For a decision tree to classify data for machine learning and other fields)

DSM Matlab..............................

一个简单的多正弦窗的MATLAB程序，很适合初学者(A simple multi-sine window MATLAB program is suitable for beginners)

维特比译码，来自现代通信系统matlab(Viterbi Decoder, from modern communications systems matlab)

三相桥双极性PWM控制Simulink仿真，叠加一些其他信号，另加一滤波器观看PWM经过低通滤波后的波形，适合电力电子初学者(Three-phase bridge bipolar PWM control Simulink simulation, superimposed a number of other signals, plus a watch PWM filter through after the low-pass wave filter for power electronics for beginners)

NP是美国匹兹堡大学的T.L.Saaty 教授于1996年提出了一种适应非独立的递阶层次结构的决策方法，它是在网络分析法（AHP）基础上发展而形成的一种新的实用决策方法。其关键步骤有以下几个： 1 确定因素，并建立网络层和控制层模型。 2 创建比较矩阵。 3 按照指标类型针对每列进行规范化。 4 求出每个比较矩阵的最大特征值和对应的特征向量。 5 一致性检验。如果不满足，则调整相应的比较矩阵中的元素。 6 将各个特征向量单位化(归一化)，组成判断矩阵。 7 将控制层的判断矩阵和网络层的判断矩阵相乘，得到加权超矩阵。 8 将加权超矩阵单位化(归一化)，求其K次幂收敛时的矩阵。其中第j列就是网络层中各元素对于元素j的极限排序向量。 (NP is a professor at the University of Pittsburgh TLSaaty presented in 1996, an adaptation of non-independent Hierarchy of decision-making method, which is the analytic network process (AHP) formed on the basis of the development of a new and practical decision-making method . The key steps are the following: A determining factor, and a network layer and control layer model. 2 create a comparison matrix. For each of the three types of indicators in accordance with normalized columns. 4 find the maximum for each comparison matrix eigenvalue and the corresponding eigenvectors. 5 consistency test. If not satisfied, then the comparison to adjust the corresponding matrix elements. 6 will each feature vector units of (normalized), to determine the composition of matrix. 7 to determine the control layer and network layer to determine matrix matrix multiplication, to be weighted super-matrix. 8 of the weighted super-matrix units of (normalized), seeking the powe)