Cai Circuit MATLAB Simulation Code-Chaos Attractors in Python Scripts
蔡氏电路 MATLAB 仿真代码 混沌吸引子适用于某些 三阶混沌系统 的 Python 脚本 (Lorenz吸引子、Nose-Hoover振荡器、Rossler吸引子、Rikitake模型、Duffing映射等)。主要资讯包括标题分析和 建模混沌系统。\\作者:亚历山大·卡皮塔诺夫。接触 lang 项目的 Python 3 初版日期为 2019年5月30日,执照为 GNU GPL 3.0。\\### 依存关系\项目要求:\- Python(>= 3.6)\- NumPy(>= 1.19.0)\- 科学(>= 1.5.1)\- 熊猫(>= 1.1.0)\- Matplotlib(>= 3.2.2)\- Pytest(>= 5.4.3)\- 预先提交(>= 2.6.0)\\### 混沌模型示例\#### 洛伦兹吸引子:\\[ dx/dt = sigma * (y - x) \] \[ dy/dt = rho * (x - z) - y \] \[ dz/dt = x * y - beta * z \] \其中 sigma = 10,rho = 28,beta = 8/3。\\#### 罗斯勒吸引子:\\[ dx/dt = -(y + z) \] \[ dy/dt = x + a * y \] \[ dz/dt = b + z * (x - c) \] \其中参数 a、b、c 为指定常数。
Matlab
0
2024-11-03
MATLAB Code for Droplet Simulation in IST
This MATLAB code is designed for simulating a droplet in the IST framework. The code models the dynamics of a water droplet, accounting for its behavior under various physical conditions. The simulation visualizes the droplet's surface tension and interaction with external forces, providing a detailed view of how droplets behave in different environments.
Matlab
0
2024-11-05
MATLAB Othello Game Code with AI A Classic Reversal Game Implementation
本程序实现了经典的黑白棋(Othello)游戏,并且带有AI对战功能。所有的.c文件需要先用mex编译。你可以在MATLAB命令窗口中执行以下命令进行编译:
mex getAllValid.cmex utility_c.c
编译完成后,运行主程序 main.m。程序启动后,你将被要求选择“人类与人工智能”或“人工智能与人工智能”对战模式。如果选择“Human vs AI”,你可以选择扮演黑子或白子。在侧边栏中,你可以访问一些游戏设置和选项,如加载或保存游戏状态。你还可以通过滑动条或者文本框修改游戏的时间线,包括AI的思考时间,默认情况下,AI有1秒钟思考时间,但可以随时调整。游戏结束后,你会看到当前的分数,并且会询问是否重新开始新的一局。如果选择“是”,游戏将重新开始;如果选择“否”或“取消”,当前游戏状态将保留。
我选择在MATLAB中实现这个程序,主要是因为觉得这会很有趣,另外,我也想学习如何使用mex来处理C语言代码与MATLAB的接口。
Matlab
0
2024-11-05
Wireless Communication Simulation BPSK Results and Code
在本仿真中,我们探讨了BPSK(二进制相位键控)的仿真结果及其相关代码。通过实验,我们可以观察到BPSK在不同信噪比下的性能表现。以下是仿真的核心代码示例:
# BPSK Simulation Code
import numpy as np
import matplotlib.pyplot as plt
# Parameters
N = 1000 # Number of symbols
SNR_dB = 10 # Signal to Noise Ratio in dB
# Generate random binary data
data = np.random.randint(0, 2, N)
# BPSK Modulation
bpsk_signal = 2*data - 1
# Add noise
noise = np.random.normal(0, np.sqrt(1/(2*(10**(SNR_dB/10)))), N)
received_signal = bpsk_signal + noise
# Plot
plt.plot(received_signal)
plt.title('Received BPSK Signal')
plt.xlabel('Sample Index')
plt.ylabel('Amplitude')
plt.grid()
plt.show()
这个示例展示了BPSK调制及其在噪声环境下的表现。
Matlab
0
2024-10-31
Adaptive-Notch-Filter-Simulation-Code
本资源提供自适应陷波器的MATLAB仿真代码,包括级联型与并联型两种结构,实现方式灵活多样。用户可以选择单中心频率或多中心频率的功能,用于实现信号的自适应陷波和滤波。仿真结果显示,代码性能优秀,滤波效果良好,非常适合对信号处理有需求的工程师和研究人员。
Matlab
0
2024-11-05
Matlab Face Matching Code-MOT Paper List Multi-Object Tracking Papers
Matlab人脸匹配代码 MOT纸单多对象跟踪的论文清单(大量借阅:)
基准测试:- MOT2015基准,MOT16:米兰,安东,劳拉·莱·Tyk斯,伊恩·里德,斯特凡·罗斯和康拉德·辛德勒的多对象跟踪基准。 arXiv预印本arXiv:1603.00831(2016)。- MOT-2017基准测试,朱鹏飞,温龙吟,小编,凌海滨和胡庆华。 arXiv预印本arXiv:1804.07437(2018)。- UA-DETRAC基准,- MOTS:多对象跟踪和细分 CVPR-2019。Voigtlaender,Paul,Michael Krause,Aljosa Osep,Jonathon Luiten,Berin Balachandar Gnana Sekar,Andreas Geiger和Bastian Leibe。- KITTI数据集,基准评估:- Matlab:Python:评论文件:arXiv预印本arXiv:1409.7618(2014)。- 罗,罗文涵,邢俊亮,安东·米兰,张晓琴,刘炜,赵晓薇和金泰K。 arXiv预印本arXiv:1802.06897(2018)。
Matlab
0
2024-11-06
Modeling Toolbox for MATLAB Resources
不错的东西,建模资源 matlab工具箱。
Matlab
0
2024-11-04
MATLAB_Integration_of_C_Code_for_Decel_Sim_Pulse_Stark_Decelerator_Simulation
MATLAB集成的C代码#####减速器模拟器大约2015年5月由D.雷恩斯#####书面1/16/18 decel-sim在JILA的Ye实验室中模拟脉冲式Stark减速器。它替代了撰写时可以在以下位置找到的C++代码库:jilafile.colorado.edu/scratch/ye/common/ColdMolecules/Simulations/mclass_dave/。先前的代码库主要由Brian Sawyer和Eric Hudson编写,尽管不确定Ben Stuhl可能也做了多少工作。我成功完成了这项工作,但由于集成了绘图和模拟数据分析功能,因此发现使用MATLAB可以最快地完成科学工作。在撰写时,也可以在jilafile上找到decel-sim:jilafile.colorado.edu/scratch/ye/common/ColdMolecules/Simulations/MatlabSim/decel-sim/。密钥代码文件名为simd。
Matlab
0
2024-11-04
Matlab Scheduling Algorithm Simulation Code-CSC417Physics-Based Animation
Course Information
Course Title: Matlab Scheduling Algorithm Simulation Code - CSC417 / CSC2549: Physics-Based Animation
Instructor: Professor [Name] (Contact via email)
Office Hours: Tuesdays 5:00 PM - 6:00 PM via Zoom (Link will be sent to registered students)
Teaching Assistant (TA): Vismay Modi, Honglin Chen
Course Description:This course aims to introduce students to the fundamental mathematical and algorithmic techniques required for effective numerical simulation of physical phenomena, such as rigid bodies, deformable bodies, and fluids. The focus is on developing algorithms that produce visually compelling representations of physical systems. Topics include the mathematics for describing the motion of physical objects, discretization techniques, and efficient numerical methods for solving discrete equations.
Prerequisites:- C/C++ programming- Linear algebra- Calculus- Numerical methods
Students should be familiar with basic linear algebra, geometry, and vector calculus. Basic programming skills in C++ are assumed. (Strongly recommended: Multivariable calculus.)
Useful Resources: Please refer to the course materials for recommended readings and additional resources.
Zoom Office Hours:- Tuesday: 4:00 PM - 5:00 PM- Wednesday: 2:00 PM - 3:00 PM(Links will be sent via email to registered students)
Discussion Board: Access course discussion board for assignments and discussions.
Summary
CSC417 provides the theoretical and practical foundation for developing physics-based animation algorithms using Matlab. Students will learn to simulate and represent complex physical systems like rigid bodies, deformable bodies, and fluids. The course emphasizes the application of numerical methods to solve physical equations for real-time simulations.
Matlab
0
2024-11-06