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experiment6
对图像进行在频域的变换，例如使相位为0，使幅值为0等(The image transform in the frequency domain, such as phase 0, the amplitude is 0)
- 2012-05-31 22:55:12下载
- 积分：1
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jOINpARSER
Join Parser extends Parameters Parser.
- 2014-01-13 18:03:49下载
- 积分：1
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DRSHE
Dynamic Range Separate HE
- 2013-08-21 09:52:22下载
- 积分：1
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damp_motion1
damp_motion1资料的详细功能、包含内容说明(damp_motion1 information, including the content description)
- 2012-09-09 05:23:17下载
- 积分：1
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MATLABnumericalcode
matlab常用的程序算法集，对学习matlab数值计算有很大的帮助(set of commonly used program algorithm matlab, matlab numerical learning a great help)
- 2010-11-04 17:59:14下载
- 积分：1
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随机集目标跟踪包
用于实现基于随机有限集目标跟踪的matlab程序，拥有详细注释(Matlab program for JPDA implementation, with detailed annotations)
- 2021-01-01 19:08:57下载
- 积分：1
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MIMO
这是我做的一个MIMO系统，希望能给大家提供帮助与参考，运行uni_start(This my own matlab code about mimo system,please run uni_start
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- 2009-06-01 17:27:31下载
- 积分：1
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Matlab-and-numerical-analysis
这里是matlab与数值分析的学习资料，对于初学者非常有用。(Here is the matlab and numerical analysis of learning materials, is very useful for beginners.
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- 2012-03-22 11:16:04下载
- 积分：1
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Prony-Toolbox
Prony的matlab工具箱，很详细，使用它可以对信号进行prony变换和分析。(Prony matlab toolbox,the signal can be prony transformation and analysis.)
- 2020-06-30 15:00:01下载
- 积分：1
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D_star_PathPlanning-master
说明： 近年来，基于启发式的多目标优化技术得到了很大的发展，研究表明该技术比经典方法更实用和高效。有代表性的多目标优化算法主要有NSGA、NSGA-II、SPEA、SPEA2、PAES和PESA等。粒子群优化(PSO)算法是一种模拟社会行为的、基于群体智能的进化技术，以其独特的搜索机理、出色的收敛性能、方便的计算机实现，在工程优化领域得到了广泛的应用，多目标PSO(MOPSO)算法应用到了不同的优化领域[9~11]，但存在计算复杂度高、通用性低、收敛性不好等缺点。
多目标粒子群（MOPSO）算法是由CarlosA. Coello Coello等在2004年提出来的(In recent years, heuristic-based multi-objective optimization technology has been greatly developed, and research shows that this technology is more practical and efficient than classical methods. Representative multi-objective optimization algorithms mainly include NSGA, NSGA-II, SPEA, SPEA2, PAES and PESA. Particle Swarm Optimization (PSO) algorithm is an evolutionary technology based on swarm intelligence that simulates social behavior. With its unique search mechanism, excellent convergence performance, and convenient computer implementation, it has been widely used in the field of engineering optimization. The objective PSO (MOPSO) algorithm is applied to different optimization fields [9~11], but it has shortcomings such as high computational complexity, low versatility, and poor convergence.
The multi-objective particle swarm optimization (MOPSO) algorithm was proposed by Carlos A. Coello Coello et al. in 2004)
- 2021-04-17 17:50:13下载
- 积分：1
