Computational-Electromagnetics

It is an important ebook for who teach multisim software.It consists of total 20 chapters.

Large Area DEM Generation Using Airborne LiDAR Data and Quality Control

激光作为21世纪四大发明之一，在各个行业积极发挥着作用，这里介绍了各种常用激光器的参数和应用范围(Laser as a 21st century one of the four great inventions in various industries to actively play a role in a variety of commonly used lasers presented here the parameters and scope of application)

精确心电信号ＥＣＧ的信号处理，生物医学工程的学习材料(ECG accurate ECG signal processing, and biomedical engineering learning materials)

bpsk通过噪声信道然后通过双边带调制，然后解调(bpsk through the noisy channel and then through bilateral band modulation, and demodulation)

wavelet matlab example，you can learn wavelet analysis from these examples.(wavelet matlab example, you can learn wavelet analysis from these examples.)

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)

文章展示了一种新的方法用于功率系统中短期负载预测。提出的方案使用混沌时间序列分析基于确定性混沌去捕捉复杂的负载行为特征。确定性的混沌允许我们重构一个时间序列并决定输入的变量个数。这篇文章描述了混沌时间序列对日间功率系统峰值的分析。确定性混沌的非线性图形通过多层感知器的神经网络得到。提出的方案在一个例子中具体阐述。(This paper presents a new approach to short-term load forecasting in power systems. The proposed method makes use of chaos time series analysis that is based on deterministic chaos to capture characteristics of complicated load behavior. Deterministic chaos allows us to reconstruct a time series and determine the number of input variables. This paper describes chaos time series analysis of daily power system peak loads. The nonlinear mapping of deterministic chaos is identified by the multilayer perceptron of an artificial neural network. The proposed approach is demonstrated in an example.)

说明：  此程序是自适应波束图中的主波束的天线方向图 函数调用了sinc函数 (This procedure is adaptive beamforming map of the main beam of the antenna pattern function call the sinc function)

关于迭代学习算法，分析了收敛速度,开闭环二阶迭代学习控制算法(The Analysis of Convergence Speed for an Openand Closed Loop Second Order Iterative Learning Control Algorithm)