small-signal-stability

duobinary conversion for agiven input symbols

针对单轴燃气轮机这样大型复杂且具有极强非线性的热力系统,利用Matlab/Simulink对某型单轴燃 气轮机系统进行了仿真,并采用自适应多模型广义预测控制的先进控制方法对转速控制器进行了仿真分析。 仿真表明,该控制方案对燃气轮机的转速控制取得了很好的效果,具有实际应用价值,为燃气轮机的转速控制 提供了一种新的思路 (failed to translate)

基于MATLAB的电力系统潮流计算程序设计的4节点P-Q分解法潮流计算程序原代码(Original code based on MATLAB power flow calculation program designed 4-node PQ decomposition flow calculation procedures)

分数付利叶变换的第二种算法 matlab程序(The m-file frft2.m computes the fast fractional Fourier transform following the algorithm)

说明：  BP神经网络算法，BP(back propagation)神经网络是一种按照误差逆向传播算法训练的多层前馈神经网络，是应用最广泛的神经网络。(BP (back propagation) neural network is a kind of multilayer feedforward neural network which is trained according to the error back propagation algorithm. It is the most widely used neural network.)

模糊自适应PID控制，PID参数整定，模糊规则，模糊推理(fuzzy PID control)

规则障碍物环境下的机器人路径规规划matlab源码！ (Robot path planning rules obstacle environment planning matlab source code!)

在机动目标跟踪中，机动目标模型是机动目标跟踪的基本要素之一，一般希望机动目标模型能准确表征目标机动时的各种运动状态。比较常用的模型有匀速运动(CV)模型、匀加速运动(CA) 模型、时间相关模型（Singer）和机动目标“当前”统计模型。上述模型均采用机动频率表征目标的机动情况。在应用当中，通常采用固定的机动频率，这就表示机动目标的机动时间是一定的，而实际上机动目标的机动时间是不断变化的，也就是说机动频率是不断变化的，采用固定机动频率必然会带来误差。采样周期在0.5—2S时，机动频率越小跟踪精度越高[1]，但机动频率仍然是固定值。本文提出的基于神经网络的机动频率自适应调整方法可以使机动频率随机动而变化，从而提高状态估计的准确性，提高跟踪精度。本文将小波神经网络用于机动目标跟踪中机动频率的自适应调整，该算法对机动目标“当前”统计模型中的机动频率进行实时修改, 从而自适应的改变机动频率,使跟踪算法与目标的真实状态更接近。该算法采用小波神经网络的离线训练，实时性好。(The maneuver of the maneuvering target is uncertain. The maneuvering frequency is constantly changeable, but traditionally it is beforehand determined as a constant based on the target state estimation in the state model of the maneuvering target. The maneuver of the maneuvering target makes the kinematics equation of the target model mismatch with the practical motion model and the tracking error will be increased. Based on the advantages of the self-learning, the rapid convergence rate and the nonlinear approximation ability of the wavelet neural network, it was put forward to be used in the field of target tracking in the paper. The new residual is used as the input of the wavelet neural network, the output of the network is used to adjust adaptively the maneuvering frequency of the CS model. The algorithm is more close to the real state of the target. The simulation results showed that tracking error can be reduced and the tracking accuracy can be improved.)

Owen2008年出版的Computational methods for plasticity: theory and applications一书中的源程序(Owen2008 published Computational methods for plasticity: theory and applications a source book)

用MATLAB实现有限长滤波器的源代码，东南大学第二次实验(MATLAB realization of finite length filter with the source code, Southeast University, the second experiment)