shiyanshishuju

Matlab参考书（word版），分章节，较PDF清晰多了。(Matlab reference (word version), sub-chapters, much clearer than the PDF.)

采用最小二乘法，样条差值等各种方法进行数值计算，并画出相应的图形(Using the least square method, spline method of difference and other numerical calculations and draw the corresponding graph)

辨识信号白噪声的产生，新手必看。希望对大家帮助(Identification signal generating white noise, Xinshoubikan)

通过一个数字信号功率谱分析程序设计的实例，详细地介绍了Visual c++和Matlab通过 engine引擎接口进行混合编程的技术，在信号处理的软件开发中采用这种方法可以提高软件开发 的效率和可靠性。(Digital signal through a power spectral analysis of programming examples, detailed description of the Visual c++ and Matlab engine through the engine mixed programming interface technology, signal processing in software development this approach can improve the efficiency of software development and reliable sexual.)

极坐标系下电力系统潮流计算Matlab版源程序(Matlab version of the source of power flow calculation in polar coordinates)

介绍国内外机械故障诊断技术的发展情况，并列举了应用实例。(Describes the development of domestic and foreign machinery fault diagnosis technology, and examples of its applications.)

数字图像处理matlab源码,对初学者很有帮助，(the matlab source code of digital image processing. )

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)

Gaussian Correction for Gravimetry processing in matlab

说明：  MDPSK在AWGN，瑞利等信道下的性能仿真比较(MDPSK in AWGN, Rayleigh and other channels compared the performance of simulation)