package_emd

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)

几种模糊度比较方法，提出优化的模糊度方法。matlab程序(Several ambiguity comparison method, proposed ambiguity optimized method. matlab program)

L1-SVD与OMP算法在重构稀疏信号上的比较(L1-SVD and OMP for sparse signal reconstruction)

matlab产品手册，详细介绍了Matlab的关键部分和组成，对了解产品的特性很有帮助(matlab product manuals, detailing a key part of Matlab and composition, very helpful in understanding the characteristics of the product)

说明：  高等应用数学问题matlab求解，包括例题的全部代码 很适用的 (Matlab solving the problem of Higher Mathematics, including examples of all the code is applicable)

this is file transport neutron

OFDM 对频偏非常敏感，文件主要是基于导频方法的频偏估计(OFDM is very sensitive to frequency offset, frequency offset file is mainly based on the pilot estimates)

考虑你在哪里不同的传感器，桥上两侧的汽车造成的振动记录收集数据的情况。当你分析这些信号，则可能需要对齐。假设你有3个传感器以相同的采样速率工作，他们是造成同一事件的测量信号。(Consider a situation where you are collecting data different sensors, recording vibrations caused by cars on both sides of a bridge. When you analyze the signals, you may need to align them. Assume you have 3 sensors working at same sampling rates and they are measuring signals caused by the same event.)

Sheffield遗传算法工具箱的matlab代码(Sheffield genetic algorithm toolbox matlab code)

ex5_1 I-型线性相位FIR滤波器 ex5_2 II-型线性相位FIR滤波器 ex5_3 III-型线性相位FIR滤波器 ex5_4 IV-型线性相位FIR滤波器 ex5_5 矩形窗频响 ex5_6 希尔伯特变换器设计－汉宁窗 ex5_7 低通滤波器设计－汉明窗 ex5_8 带通滤波器设计－布莱克曼窗 ex5_9 低通滤波器设计－凯塞窗 ex5_11 频率采样技术：低通，朴素法 ex5_12 频率采样技术：低通, 最优法T1 & T2 ex5_13 频率采样技术：带通, 最优法T1 & T2 ex5_14 频率采样技术：高通, 最优法T1 ex5_15 频率采样技术：差分器 ex5_16 频率采样技术： 希尔伯特变换器 ex5_17 利用Parks-McClella算法设计低通滤波器 ex5_18 用PM算法进行的带通滤波器设计 ex5_19 用PM算法进行的高通滤波器设计 ex5_20 用PM算法进行的阶梯滤波器设计 ex5_21 用PM算法进行的差分器设计 ex5_22 用PM算法进行的希尔伯特变换器设计(ex5_1 I-type linear phase FIR filter ex5_2 II-type linear phase FIR filter ex5_3 III-type linear phase FIR filter ex5_4 IV-type linear phase FIR filter rectangular window frequency response ex5_5 Hilbert ex5_6 converter design- Hanning window low-pass filter design ex5_7- Hamming window ex5_8 bandpass filter design- Blackman window ex5_9 low-pass filter design- Kaiser window ex5_11 sampling frequency: low-pass, a simple method ex5_12 sampling frequency: low-pass, optimal method T1 & T2 sampling frequency ex5_13: band-pass, optimal method T1 & T2 ex5_14 sampling frequency: high-pass, optimal method T1 sampling frequency ex5_15: differentiator sampling frequency ex5_16: Hilbert converter Parks-McClella use ex5_17 algorithm design low-pass filter PM algorithm ex5_18 with the band-pass filter design PM algorithm ex5_19 with the high-pass filter design PM algorithm used ex5_20 ladder filter design PM algorithm used ex5_21 differential design PM al)