flux_density2_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)

结合pso的fcm算法，可以计算最佳聚类个数和具体的聚类位置。(fcm with pso)

用于MATLAB 6.0 (R12)环境 Dijkstra最短路由算法源代码 ( MATLAB 6.0 (R12) Dijkstra Shortest Path Routing )

说明：  matlab 编程实现人体跟踪与检测编程实现人体跟踪与检测(matlab)

for rocket engine calculation.(rocket calculation.)

产生信号序列向量st,并显示st的时域波形和频谱 st=mstg 返回三路调幅信号相加形成的混合信号，长度N=800( Generated signal sequence vector st st time-domain waveform and the spectrum st = mstg return three AM signals are added to form the mixed-signal length N = 800)

灰色系统gm（1，1）模型的matlab程序，可以用于灰色预测。(Grey gm (1,1) model matlab program can be used for gray prediction.)

说明：  关于数字水印的一些代码 基于离散余弦变换 (on digital watermarking code based on the Discrete Cosine Transform)

这是一个bp的神经网络反演的matlab程序(BPBPBBBBBBBBPPPPPPPPPPPPp)

dc motor kalmen filter desgn