CuckooOptimizationAlgorithm

求解出在最小均方误差滤波器单位冲激函数h(n)。求解过程需要通过利用循环嵌套的编程思想，比较在逐次增加滤波器阶数的过程中得到的最小均方误差与最初设定的最小均方误差的阈值，当达到要求时，可以进一步确定滤波器的阶数。(how to use this function: [hx,hy]=wiener_ch2(w,N) )

超声波系统下的FFT仿真程序,可以将主要频率的波长滤波出来(FFT simulation program of ultrasonic system, can filter out the main frequency wavelength )

最优化中一维搜索方法中的黄金分割法和Fibonacci法程序(Optimization of one dimensional search v one dimensional search method in optimization of the golden section method and the Fibonacci method program)

包括了qpsk gmsk msk fsk qam ask psk oqpsk ssb等各种常见的调制方式的详细的调制程序(Includes qpsk gmsk msk fsk qam fsk psk dpsk ssb other common modulation scheme of a modulation procedure detailed)

移相全桥控制程序，带pi调节，闭环控制，基于lcl结构的拓扑结构(Phase-shifted full-bridge control program, with pi regulation, closed-loop control, structure-based topology lcl)

说明：  dco-ofdm调制解调程序，非常实用的代码(case for DCO-OFDM system)

Bifurcation Diagram of Circular map

Document related to water management

说明：  基于MATLAB的BP神经网络非线性映射能力实现图像压缩。(MATLAB Based on BP neural network nonlinear mapping capability for image compression.)

粒子群优化工具箱，采用Matlab编写的PSO程序工具箱(Development Notes for psopt toolbox Future plans (in no particular order): * Performance improvement: Automatically check for existence of constraints, skip boundary-checking if unconstrained. * Performance improvement: Automatically vectorize fitness functions supplied by user, if not already vectorized. * Performance improvement: Detect and eliminate dependent (i.e. redundant) linear constraints. * Performance improvement: Automatically choose "penalize" versus "soft" constraint handling method based on type of constraints in problem. If any equality constraints exist, using "penalize", otherwise default to "soft". If "soft", automatically switch to "penalize" if more than a given percentage of particles (initial or interim) are infeasible. * Feature: An output function defined by options.OutputFcns that can save current swarm state in a file which can be reloaded later as a problem structure, in case of a system crash. * Feature: Implement multiobjective optimization option)