arqr

遗传算法，非常经典，大家相互交流，大家有好的程序源代码也上传啊(Genetic algorithm (ga), very classic, we communicate with each other, everyone has a good program source code also uploaded)

Single Perceptron : Linear Discriminants

variabel acak diskrit, percobaan sistem komunikasi dengan menggunakan software matlab

说明：  仿真滚降系数为0.22的平方根升余弦滤波器的MATLAB程序.(Simulation of roll-off factor of 0.22 square root raised cosine filter of the MATLAB program.)

find the area of circle, temprature(celcius-far), logic design in matlab for 3 variable

power electric simulation full bridge

matlab最短路的贪心算法，用VC++实现，把ShortEst.dll复制到matlab工作文件夹运行（先要运行mex-setup，关联VC与MATLAB）调用方法如 a = [-1,2,3 2,-1,4 3,4,-1] ShorstEst(a) 即可(matlab most short-circuit the greedy algorithm, using VC++ to achieve, and copy it to ShortEst.dll working folder matlab run (first run mex-setup, associated VC with MATLAB) method call, such as a = [-1,2,3 2,-1,4 3,4,-1] ShorstEst (a) can)

线性代数实践及MATLAB入门 本书是根据“用软件工具推向线性代数教学”的指导思想，参照美国1992-1997国家科学基金项目ATLAST的思路，编写成的线性代数补充教材，其目的是补充我国现有教材的的缺陷。它分为两篇，第一篇介绍线件代数所用的软件工具MATLAB语言，第二篇介绍线性代数实践。本书可作为大学本科线性代数的配套教材，也可作为广大理工、经管领域教师、工程师和研究生的参考读物。(Introduction to Linear Algebra practice and matlab This book is based on the guiding ideology"use of software tools into the teaching of linear algebra," , with reference to the ATLAST ideas of U.S. National Science Foundation(1992-1997) , written as a linear algebra supplementary materials, the purpose is to supplement our existing materials defects. It is divided into two parts, the first introduces line of pieces of software tools used in algebraic MATLAB, the second introduces linear algebra practice. )

扩频信号产生，频谱显示............................(Spread spectrum signal generator, spectrum display)

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)