trying

This function simulates damages in the received frame corresponding to the loss of one NALU (i.e. slice) given a slicing mode and the slice to be lost

GMF（Graphical Modeling Framework）是Eclipse的一个开源项目，它在结合了EMF和GEF的 基础上，为基于模型的图形化编辑器的开发提供了一个功能强大的框架，开发人员可以采用建 模的方式很容易的生成高质量的代码框架。(GMF (Graphical Modeling Framework) Eclipse is an open source project, it combines the foundation on EMF and GEF, provides a powerful graphical editor framework for model-based development, developers can adopt the modeling approach easily generate high-quality code framework.)

关于模拟纳米粒子自组装系统的I-V曲线matlab(matlab code for Self-assembly of nanoparticles on the simulated IV curve of the system )

matlab 经典教程 从入门到精通 实例讲解 非常经典 值得收藏(matlab classic tutorial on the very classic examples from entry to the proficient worth collecting)

matlab 包含优化问题试验、微分议程试验、代数实验和综合试验等 (matlab optimization problem that contains test, differential agenda test, algebra test and integrated test)

这是混沌时间序列预测的工具箱，里面有测量关联维数的GP方法，还有测量延迟时间t的时序法，有C_C方法这种可以来测量两者的方法。(This is the chaotic time series prediction toolbox, which has measured correlation dimension GP method, as well as measuring the delay time t timing method, there C_C Method This method can be used to measure both.)

matlab 通信原理 sa函数波形仿真 周期矩形脉冲幅度谱 含源码(sa communication theory matlab function waveform simulation cycle rectangular pulse amplitude spectrum including source code)

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)

heed matlab protocol for wsn

线性反投影算法是一种常用的数据重建算法，本程序中包含线性反投影算法、奇异值分解算法、正则化算法等算法。(Linear Back Project algrithm.)