System-Dynamic-Model

Digital Wireless Communication

front tracking method for free surface or structure movement.

系统传输函数 用于系统传输简单模拟 了解传输过程(transfer in matlab)

画出每个IMF分量及最后一个剩余分量residual的图形 画出每个IMF分量及剩余分量residual的幅频曲线 用Hilbert变换直接求该信号的瞬时频率 计算HHT时频谱和边际谱(Draw each IMF component and the last one remaining residual component graphics draw each IMF component and the amplitude of the remaining component of the residual frequency curve directly seeking the instantaneous frequency of the signal with the Hilbert transform spectrum and marginal spectrum calculation HHT)

[CAL] [ENG] Numerical Analysis Using MATLAB and Spreadsheets

说明：  电力系统短期负荷预测ARMA预测数字信号处理(Power system short-term load forecasting ARMA prediction of digital signal processing)

各种kalman滤波器的设计，实现典型相关分析，含噪脉冲信号进行相关检测。( Various kalman filter design, Achieve canonical correlation analysis, Noisy pulse correlation detection signal.)

基于PID控制的永磁同步直线电机速度控制系统，输出速度能够较好的跟踪输入信号，控制效果比较理想(The speed control system of permanent magnet synchronous linear motor based on PID control can track the input signal better, and the control effect is ideal.)

peform sum of two matrices

传算法（Genetic Algorithm）是一类借鉴生物界的进化规律（适者生存，优胜劣汰遗传机制）演化而来的随机化搜索方法。它是由美国的J.Holland教授1975年首先提出，其主要特点是直接对结构对象进行操作，不存在求导和函数连续性的限定；具有内在的隐并行性和更好的全局寻优能力；采用概率化的寻优方法，能自动获取和指导优化的搜索空间，自适应地调整搜索方向，不需要确定的规则。遗传算法的这些性质，已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。它是现代有关智能计算中的关键技术(Propagation algorithm (Genetic Algorithm) is a law of evolution in biology class reference (survival of the fittest, survival of the fittest genetic mechanisms) randomized search method evolved. It was first proposed by the United States J.Holland professor in 1975, and its main feature is to operate directly on the structure of the object, the continuity of the derivative and the function limitation does not exist with global implicit parallelism inherent and better optimization capability the use of probabilistic optimization method that can automatically obtain and guidance to optimize the search space adaptively adjust the search direction, the rule does not require determined. The nature of the genetic algorithm, has been widely used in combinatorial optimization, machine learning, signal processing fields, such as adaptive control and artificial life. It is about smart modern computing key technologies)