ParticleSwarm

说明：  另一个解决无模型自适应控制问题的Simulink模型，可以作为学习MFA的参考 (Another solution to the issue of model-free adaptive control of the Simulink model can be used as reference for learning MFA)

2D Potential Flow Simulator

改进的粒子群算法在matlab中的应用，程序简单(Improved particle swarm algorithm in matlab, simple procedures)

隐马尔科夫过程预测编码，对于使用或研究隐马尔科夫模型的人会有帮助。(Hidden Markov process predictive coding, for the use of hidden Markov models or research who will help.)

Analysis and Simulation of a D-STATCOM for Voltage Quality Improvement

仿真了跳频系统中并行捕获的性能，希望对大家有帮助(parallel acquisition )

能量和过零率的计算程序 能量和过零率的计算程序(ampzcr.m － 能量和过零率的计算程序 ampzcr.m － 能量和过零率的计算程序)

QPSK传输系统在高斯信道以及瑞利衰落信道下的调制解调仿真。(QPSK transmission system in the AWGN channel and Rayleigh fading channels Modulation and Demodulation.)

Matlab Filter Implementation In this section, we will implement (in matlab) the simplest lowpass filter $displaystyle y(n) = x(n) + x(n-1), n=1,2,ldots,N $ (from Eq.$ ,$(1.1)). For the simplest lowpass filter, we had two program listings: Fig.1.3 listed simplp for filtering one block of data, and Fig.1.4 listed a main program for testing simplp. In matlab, there is a built-in function called filter3.3 which will implement simplp as a special case. The syntax is y = filter (B, A, x) where x is the input signal (a vector of any length), y is the output signal (returned equal in length to x), A is a vector of filter feedback coefficients, and B is a vector of filter feedforward coefficients. The filter function performs the following iteration over the elements of x to implement any causal, finite-order, linear, time-invariant digital filter:3.4

刘宝碇《不确定规划及应用》第4章例4.2的matlab程序,58页。内容简单，但可以有效的帮助初学者理解随机模拟的原理。(Liu anchor " uncertain Planning and Applications" in Chapter 4 Example 4.2 matlab program, 58. Content is simple, but can effectively help beginners understand the principles of stochastic simulation.)