gausdire

通信原理课程设计，包括各种调制，信道编码等。有解释，图形，源码。(Communication theory course design, including modulation, channel coding. Have explained, graphics, source code.)

surface plot for matlab

在Matlab中使用函数实现队列操作并且应用到图的宽度遍历（BFS）中(A realization of Sequence operation in Matlab. And an example applied in Breadth First Search（BFS）.)

这是个Matlab的学习的好帮手，里面有许多有用的小东西，很适合初学者。(This is a good helper to learn Matlab, which has many useful little things, it is suitable for beginners.)

天文导航方向，导航信号转化为星历表信息Matlab程序。(The direction of celestial navigation, navigation signal into Matlab ephemeris information procedures.)

最优化算法，包括各种线性优化和非线性优化问题(Optimization algorithms, including linear optimization and nonlinear optimization problems)

当线性代数联立方程组的系数矩阵为三对角阵T时，可将T分解为主对角元素为1的下三角阵L和另一个右三角阵R的积。(Simultaneous linear algebraic equations when the coefficient matrix is tridiagonal matrix T, can break down the main diagonal elements of T 1 of the lower triangular matrix L and the other right-triangular matrix R of the product.)

这是数据挖掘领域总结的十大经典算法，有助于同学们研究(This is a summary of the top ten algorithms of the field of data mining to help students)

合成孔径雷达成像算法与实现的相关代码，详细简单易懂(Code for SAR imaging algorithm and Implementation)

说明：  遗传算法（Genetic Algorithm，GA）最早是由美国的 John holland于20世纪70年代提出,该算法是根据大自然中生物体进化规律而设计提出的。是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法。该算法通过数学的方式,利用计算机仿真运算,将问题的求解过程转换成类似生物进化中的染色体基因的交叉、变异等过程。在求解较为复杂的组合优化问题时,相对一些常规的优化算法,通常能够较快地获得较好的优化结果。遗传算法已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。(Genetic algorithm (GA) was first proposed by John Holland of the United States in the 1970s. It is designed and proposed according to the evolution law of organisms in nature. It is a computational model of biological evolution process simulating natural selection and genetic mechanism of Darwin's biological evolution theory. It is a method to search the optimal solution by simulating natural evolution process. The algorithm transforms the solving process of the problem into a process similar to the crossover and mutation of chromosome genes in biological evolution by means of mathematical method and computer simulation. When solving complex combinatorial optimization problems, compared with some conventional optimization algorithms, it usually can get better optimization results quickly. Genetic algorithm has been widely used in combinatorial optimization, machine learning, signal processing, adaptive control and artificial life.)