Higher-Order-Spectral-

[X,Y,Z]=cylinder2(x,y,z,r,N,o) 向量X，Y，Z轴定义圆柱面中心线 和矢量r定义圆柱面半径，并已 为的x，y，z的长度相同 N是周围围点的数量。默认值 为N= 100。 Ø 定义了矩阵圆柱generatix（圆圈）椭圆 表面。其内容以0和1之间的值，并适用于 小学和中学的母线轴。值的defeault Ø =的（长（x），2）。 矩阵X，Y，Z轴确定圆柱面，冲浪（的X，Y，Z）的显示器 圆柱面。( [X,Y,Z]=cylinder2(x,y,z,r,N,o) Vectors x, y, z define the central line of cylindrical surface and vector r defines the radius of cylindrical surface, and has the same length as x, y, z. N is the number of points around the circumference. The default value is N = 100. Matrix o defines ovality of the generatix (circle) of cylindrical surface. Its elements take values between 0 and 1 and apply to the primary and secondary axis of generatrix. The defeault values are o=ones(length(x),2). Matrices X, Y, Z define the cylindrical surface, surf(X,Y,Z) displays the cylindrical surface. )

初始化粗粒度序列,为计算脑电信号非线性参数——复杂度的Matlab程序(Initialization sequence of coarse-grained, for the calculation of the nonlinear parameters of the EEG- the complexity of the Matlab program)

杜芬系统跳跃现象 小参数 时间步长 以点或线画图可调(Duffing jumping phenomenon, the small parameter can be modulated and the time step can be set by yourself )

对于单次提取的诱发响应，本程序提供了一种用matlab实现消除诱发响应潜伏期的影响的快捷有效的方法(Eliminate latency of evoked response)

雷达系统仿真,该雷达具有数字化正交解调、数字脉冲处理、固定目标对消、动目标检测（MTD）、和恒虚警（CFAR）处理等功能(Radar system simulation, the radar has a digital quadrature demodulation, digital pulse processing, fixed target for elimination, moving target detection (MTD), and CFAR (CFAR) processing functions)

used to filter the latent state variable

metlab中的GUI实验内容，详细罗列了实验内容(the experiments of GUI)

使用SSO求解柔性作業車間調度問題flexible job shop(Using SSO to solve flexible job shop scheduling problem flexible job shop)

Synthetic Aperture Radar Simulation extended target as the shape of tank using four different types of Signals LFM Signal Conventional OFDM CP-based OFDM Random Noise Signal

说明：  遗传算法是计算数学中用于解决最佳化的搜索算法，是进化算法的一种。进化算法最初是借鉴了进化生物学中的一些现象而发展起来的，这些现象包括遗传、突变、自然选择以及杂交等。遗传算法通常实现方式为一种计算机模拟。对于一个最优化问题，一定数量的候选解（称为个体）的抽象表示（称为染色体）的种群向更好的解进化。传统上，解用二进制表示（即0和1的串），但也可以用其他表示方法。进化从完全随机个体的种群开始，之后一代一代发生。在每一代中，整个种群的适应度被评价，从当前种群中随机地选择多个个体（基于它们的适应度），通过自然选择和突变产生新的生命种群，该种群在算法的下一次迭代中成为当前种群。(Genetic algorithm (GA) is a search algorithm used to solve optimization in computational mathematics. It is one of evolutionary algorithms. Evolutionary algorithms were originally developed by borrowing phenomena in evolutionary biology, such as heredity, mutation, natural selection and hybridization. Genetic algorithms are usually implemented as a computer simulation. For an optimization problem, an abstract representation of a certain number of candidate solutions (called individuals) (called chromosomes) evolves towards a better solution. Traditionally, solutions are represented in binary (that is, strings of zeros and ones), but other representations are possible. Evolution begins with a population of completely random individuals, and it happens from generation to generation.)