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QPSK-OQPSK
对两种调相方法进行分析比较,通过MATLAB编程对比两种方式的区别与联系(Phase modulation of two methods of analysis and comparison, through MATLAB programming in two ways the difference between contrast and contact)
- 2008-04-23 22:16:59下载
- 积分：1
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QPSKsimulation
这是我在网上找到的，里面比较详细的介绍了QPSK的仿真。(This is what I found on the Internet, where a more detailed introduction to the QPSK simulation.)
- 2007-01-13 22:49:55下载
- 积分：1
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cpc
uploaded the polar codes for cooperative relay networks and the same can be used for compression
- 2013-08-24 21:35:56下载
- 积分：1
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16qam_ofdm_source_code
16QAM编译码程序，在信号调制过程中是不可缺少的成分(16QAM encoding and decoding process, in the course of signal modulation is an indispensable ingredient)
- 2013-11-27 09:37:27下载
- 积分：1
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matlab
Computing with Mathematica, 2nd edition.pdf
- 2010-12-14 04:41:35下载
- 积分：1
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KalmanGPS
It uses kalmanf(s) function to calculate GPS error variance.
- 2010-12-22 18:40:39下载
- 积分：1
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Introduction-to-Matlab
matlab概述书籍，matlab编程入门(the matlab Overview books, matlab programming entry)
- 2013-01-29 11:34:29下载
- 积分：1
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SVD-PCA-eig
本程序详细区别了matlab中pca、svd、eig三个函数的区别和联系。对于学习pca有极大帮助(This program detailing the differences between the differences and connections in matlab pca, svd, eig three functions. Pca great help for learning)
- 2021-04-25 13:18:46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
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NCPSO
matlab 优化问题 小生境和蚁群算法的结合 能运行(matlab optimization niche and the combination of ant colony algorithm can run)
- 2010-12-06 16:46:16下载
- 积分：1
