这里提供了基于FDTD方法的四个MATLAB代码示例,逐步深入探讨电磁场中的Ex和Hy场分量在z方向的传播,包括吸收边界条件(ABC)的应用、脉冲与介质相互作用的模拟,以及正弦波与介质相互作用的仿真。
基于FDTD方法的1D电磁波仿真MATLAB代码
相关推荐
MATLAB电磁波项目 - Electromagnetic Waves MATLAB Project
这个项目要求在特定设计频率下设计微带线四分之一波变压器。由休斯顿大学杰克逊教授(2020年秋季)完成,项目专注于应用电磁波(ECE 3317)。存储库仅用于项目归档,包含MATLAB代码用于生成绘图。
Matlab
0
2024-08-18
1D AEM反演的Matlab Trans-D代码示例
用于1D AEM(或任何1D模型)反演的Matlab Trans-D代码示例,运行仅需在Matlab路径中包含/ include目录和子目录,按照编号顺序运行命名脚本。基于Blatter等人(2018)和Ray等人(2013,2012)的工作,来自机载瞬态电磁数据的跨维贝叶斯反演泰勒冰川。
Matlab
0
2024-09-26
电磁波辐射图模拟及天线特性分析
利用Matlab进行电磁波辐射模拟,探讨二半波振子同相激励下的场强分布及天线特性。设置振子间距为波长的一半,计算其在E面和H面的方向性函数,并绘制辐射方向图。
Matlab
2
2024-08-01
电磁场与电磁波(第四版)课后答案
电磁场与电磁波(第四版)课后答案由谢处方编写,涵盖了电磁场、电磁波、Maxwell方程组、波导和天线等内容。
Access
4
2024-05-15
MATLAB 电磁场及电磁波可视化:电力线与等势线分析
利用 MATLAB 对电磁场与电磁波进行可视化处理,深入探讨电力线和等势线的分布规律。通过代码实现,将抽象的电磁场理论以图形方式呈现,并结合相关概念解析,帮助读者更直观地理解电磁场的性质和行为。
Matlab
1
2024-05-30
Wasserstein距离计算代码1D中1-和2-Wasserstein距离的Matlab实现
这段代码能够计算在给定样本下,两个均匀概率分布之间的1-Wasserstein距离和2-Wasserstein距离。从图形上来看,它衡量了输入向量的(归一化)直方图之间的距离。详细信息可参阅GitHub存储库。
Matlab
0
2024-09-29
Optimized Overlap-and-Add 1D Convolution Highly Optimized Implementation of Linear 1D Convolution with Best DFT Window Selection-MATLAB Development
This function implements linear 1D convolution using the overlap-and-add method. It is fully optimized, and the main loop avoids memory allocation. The function automatically computes the best DFT window for performance. It supports three output modes: Full, Same, and Valid, which align with MATLAB's conv() function. The package also includes a frequency-domain implementation and performance comparisons with two other methods.
Matlab
0
2024-11-06
1D Signal Two-Level Wavelet Decomposition and MATLAB Application
1D Signal Two-Level Wavelet Decomposition Overview
Two-Level Approximation Decomposition: The original signal is averaged every 4 values to capture the approximate components at this level.
Two-Level Detail Decomposition: The difference between every 2 consecutive values in the original signal provides the detailed components at this level.
One-Level Detail Decomposition: The difference between the odd and even-indexed values of the original signal is calculated to extract finer details.
Signal Recovery: After the decomposition, the signal can be reconstructed by combining the approximations and details from each level.
In MATLAB, you can implement these wavelet decompositions to analyze various signals effectively, applying discrete wavelet transform (DWT) functions for both decomposition and reconstruction steps.
Matlab
0
2024-11-06
When Wavelet Meets HMM WHMT for 1D Signal Denoising and Classification in MATLAB
要复制屏幕截图的结果,请运行:测试_WHMM。该脚本是参考文献[1]的实现,包括两部分:1. 一维信号去噪(9~11页) 2. 一维随机过程(RP)分类(第12页)。参考:[1] 使用隐马尔可夫模型的基于小波的统计信号处理:MS Crouse, RD Nowak, RG Baraniuk - IEEE信号处理交易,1998 - dsp.rice.edu。可在:http://scholarship.rice.edu/bitstream/handle/1911/19815/Cro1998Apr1Wavelet-Ba.PDF?sequence=1。确认:作者要感谢Justin Romberg教授的“hmt1d”工具箱和他对如何使用它的友好帮助。
Matlab
0
2024-11-03