GA-FS1

运用MATLAB解决一些城市之间的最短路程问题.(含有MATLAB源代码)(Use MATLAB to solve some of the shortest distance between cities problem. (Containing MATLAB source code))

很好的matlab学习资料，分享，希望对大家有所帮助(Matlab good learning materials, to share, we want to help)

说明：  贝叶斯网络结构学习，及参数学习K2算法matlab代码(Bayesian network structure learning and parameter learning K2 algorithm matlab code)

16QAM的MATLAB调制解调仿真，很清楚奥，很全面奥(16QAM modulation and demodulation of the MATLAB simulation, it is clear that Austria, Austrian comprehensive)

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)

对一个旋转的梁经行分析，希望通过优化，使得它的质量分配能够满足指定的频率要求（第一阶固有频率1.1左右，第二阶2.5左右，第三阶4.5左右。）(rotating beam to accomplish the frequency optimization)

A GUI for load and record and ... speech signal and sketching spectrogram.

sound operations in matlab

几个关于simulink的程序例子 希望能帮助大家(Several program examples Simulink)

fuzzy logic is a good controller