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针对梁的振动控制Matlab程序，包括输入MKC矩阵，计算固有频率，并采用Simulink进行梁的振动控制(Matlab for beam vibration control procedures, including input MKC matrix, calculate the natural frequency and vibration of beams using Simulink Control)

matlab下计算脑电信号矩阵平均功率并显示，信号采用列向量形式排列，简短有用(compute the average power of eeg matrix,short and useful)

说明：  在DCT域进行图像检索，分别采取了对DCT块的边缘类型提取以及纹理特征提取两个方法(Image Retrieval in DCT domain, DCT blocks were taken on the edge of the type and texture feature extraction method of extracting the two)

一个求解纳什交换的均衡问题的例程，运用了类似基因表示的做法，需要的请自行下载(Nash for a balanced exchange of the routines that use a similar approach expressed by the gene, Requests need to download)

线性调频信号的脉冲压缩 线性调频信号的脉冲压缩(chirps sign)

测试rastrigin 函数PSO智能算法优化程序(rastrigin PSO)

说明：  一个双向LSTM程序 Long Short Term 网络—— 一般就叫做 LSTM ——是一种 RNN 特殊的类型，可以学习长期依赖信息。LSTM 由Hochreiter & Schmidhuber (1997)提出，并在近期被Alex Graves进行了改良和推广。在很多问题，LSTM 都取得相当巨大的成功，并得到了广泛的使用。 LSTM 通过刻意的设计来避免长期依赖问题。记住长期的信息在实践中是 LSTM 的默认行为，而非需要付出很大代价才能获得的能力！ 所有 RNN 都具有一种重复神经网络模块的链式的形式。在标准的 RNN 中，这个重复的模块只有一个非常简单的结构，例如一个 tanh 层。(A bidirectional LSTM program Long short term network, commonly known as LSTM, is a special type of RNN that can learn long-term dependent information. LSTM was proposed by Hochreiter & schmidhuber (1997) and recently improved and promoted by Alex graves. In many problems, LSTM has achieved great success and has been widely used. LSTM is designed to avoid long-term dependency. Remember that long-term information is the default behavior of LSTM in practice, not the ability to acquire it at a great cost! All RNNs have a chained form of repetitive neural network modules. In the standard RNN, this repetitive module has only a very simple structure, such as a tanh layer.)

ActivedeSet(起作用集法)，这个是在二次规划中应用的(ActivedeSet)

A Low Complexity Algorithm for Proportional Resource Allocation in OFDMA Systems

脑电信号的复杂度计算，有文档和多个matlab程序实例(EEG complexity calculation, there are documents and multiple instances of matlab program)