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bppr
我编写bppr的神经网络应用程序，第一次上传(of neural network applications, the first upload)
- 2006-06-20 18:50:44下载
- 积分：1
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acs_assignment4
sliding mode control files for advanced control system
- 2011-05-16 19:55:23下载
- 积分：1
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Euler
数值计算里经典的欧拉算法的源程序，采用matlab写的，对理解欧拉算法有很大的帮助作用。(Numerical calculation in the classical Euler algorithm source code, using matlab write, for understanding Euler algorithm has a great help.)
- 2013-11-13 23:42:59下载
- 积分：1
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dt_cwt-texture
基于纹理特征的图像检索源码，通过双树复小波进行纹理特征提取(Texture-based image retrieval source, through the dual tree complex wavelet texture feature extraction)
- 2013-11-07 09:59:41下载
- 积分：1
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matlab-2010b-VS2008-Hunhebiancheng
一份学习Matlab混合编程的资料，很值得初学者看一下(Study mix program of MATLAB)
- 2015-04-13 17:29:37下载
- 积分：1
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CS_MRI
CS_MRI:压缩感知（CS）在MRI领域的应用.程序实现展示了CS在MRI的重要作用和明显效果。对于那些CS初学者有着极大的帮助。(CS_MRI:Compressive Sensing s application in MRI field. Codes realize and show the great significance of CS in MRI field.It can be of great help to those fresh in CS field.)
- 2013-05-22 10:13:22下载
- 积分：1
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paper-pdf
pdf related unit commitment
- 2019-03-14 19:07:05下载
- 积分：1
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JSBSim_MATLAB_release
This is a good file for mav simulink.
- 2010-12-20 10:55:58下载
- 积分：1
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mu_quantizer
This m-file applies uniform quantization on a given audio signal called music_ee6424.wav
It then plots waveforms and gives the Mean Square Quantization Error (MSQE)
- 2013-03-04 19:04:38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
