colletingdata

Convert IB-specific error message to RDS error message and call core completion handler.

iterative hard thresholding algorithm in Compressed Sensing

R语言统计分析软件简明教程，适合初学者深入学习(R language statistical analysis software simple tutorial for beginners in-depth study)

An example of an interactive GUI in matlab

这是一读取信号进行FM调制，可以是CMA盲均衡算法对FM信号做处理(This is a read signal to FM modulation, and can be CMA blind equalization algorithm processing the FM signal with)

使用matlab产生线性调频信号，并进行脉冲压缩处理。(Use matlab to produce linear FM signal, and pulse compression processing.)

LSB隐藏 最低有效位隐藏算法,就是8:1嵌入(Least significant bit LSB hide hiding algorithm is embedded 8:1)

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)

说明：  PFC电压模型,供大家参考使用,共同学习.(PFC voltage model for reference use, learning together.)

说明：  最大流问题，一种组合最优化问题，就是要讨论如何充分利用装置的能力，使得运输的流量最大，以取得最好的效果。求最大流的标号算法最早由福特和福克逊于1956年提出，20世纪50年代福特、福克逊建立的“网络流理论”，是网络应用的重要组成成分。(Maximum flow problem, a combinatorial optimization problem, is to discuss how to make full use of the capacity of the device to maximize the flow of transport in order to achieve the best results. The labeling algorithm for maximum flow was first proposed by Ford and Fulkerson in 1956. The network flow theory established by Ford and Fulkerson in 1950s is an important component of network application.)