-
emd
经验模态分解函数，可实现信号分解及滤波的功能。(EMD scheme which can achieve signal decomposition and noise elimanition.)
- 2009-09-14 15:39:34下载
- 积分：1
-
Grank_Nicholson
说明： 利用crank nicholson法 解一維熱傳PDE(Using crank nicholson method for solving a PDE-dimensional heat transfer)
- 2010-03-31 02:40:41下载
- 积分：1
-
AF
说明： 协作通信下AF协作模式的MATLAB仿真代码(cooperative communication)
- 2010-06-09 09:51:31下载
- 积分：1
-
Beginning-C-for-Arduino
Beginning C for Arduino
- 2013-07-17 12:48:44下载
- 积分：1
-
2011-zhang
2017-IEEE-Mining Scraper Conveyor
- 2020-06-22 00:00:02下载
- 积分：1
-
anp
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)
- 2010-01-28 09:36:45下载
- 积分：1
-
ZCR
autocov computes the autocovariance between two column vectors X and Y with same length N using the Fast Fourier Transform algorithm from 0 to N-2.
The resulting autocovariance column vector acv is given by the formula:
acv(p,1) = 1/(N-p) * sum_{i=1}^{N}(X_{i} - X_bar) * (Y_{i+p} - Y_bar)
where X_bar and Y_bar are the mean estimates:
X_bar = 1/N * sum_{i=1}^{N} X_{i} Y_bar = 1/N * sum_{i=1}^{N} Y_{i}
It satisfies the following identities:
1. variance consistency: if acv = autocov(X,X), then acv(1,1) = var(X)
2. covariance consistence: if acv = autocov(X,Y), then acv(1,1) = cov(X,Y)
- 2013-05-26 22:12:50下载
- 积分：1
-
twisting vibration
忽略系统阻尼，建立工程车辆的扭转振动模型，进行振型分析。(Ignoring the system damping, the engineering vehicle torsional vibration model is established to do the vibration analysis.)
- 2017-06-30 10:50:49下载
- 积分：1
-
smallWorldNetwork
生成beta-小世界网络
％ Authors: LuoNa, ECUST
％ v1.0 Created 30-May-2007(generation beta-small-world networks% Authors : LuoNa. ECUST% v1.0 Created 30-May-2007)
- 2007-05-31 09:38:01下载
- 积分：1
-
psam
PanCOS/PSAM
技术参考手册,对PSAM编程特别有用(PanCOS/PSAM technical reference manual, programming is particularly useful on the PSAM)
- 2010-06-17 16:01:45下载
- 积分：1
