FFT-code

In the computer science field of artificial intelligence, a genetic algorithm (GA) is a search heuristic that mimics the process of natural evolution. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimization and search problems.[1] Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. Genetic algorithms find application in bioinformatics, phylogenetics, computational science, engineering, economics, chemistry, manufacturing, mathematics, physics, pharmacometrics and other fields.

一个简单的基于MATLAB的GUI设计例子，适合初学者。(a simple GUI based on MATLAB design examples for beginners.)

科斯塔斯环基于simulink的仿真 已封装(costas loop in simulink-based simulation Encapsulation)

对图像以嵌入率为rate进行顺序LSB嵌入，然后进行卡方隐写分析(Rate on the image to be embedded in the order of LSB embedding rate, and then chi-square steganalysis)

用龙格库塔发解二阶微分方程，共三个小程序，初学者可以直接调用龙格库塔源程序(With solutions of second order differential equations Runge-Kutta hair, a total of three small programs, beginners can directly call the Runge-Kutta source)

解耦控制要求下的极点配置Matlab算法(Decoupling control requirements under the pole placement Matlab algorithm)

用随机的方法逼近函数的matlab源程序(Approximation method with random function matlab source)

stack array 1 dimension

一个弹簧、阻尼、质量系统的simulink/gui设计(A simulink springs, dampers, quality system/gui design)

单输入单输出模型预测控制算法实现--一般实现，逆响应和线性规划(SISO model predictive control- a general approach, inverse response and linear programming)