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基于改进蚁群优化的盲检测算法 被引量:2

An Blind Detection Algorithm Based on Improved Ant Colony Algorithm
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摘要 文中针对基本蚁群算法在求解过程中容易出现收敛时间过长以及易陷入局部最优解的不足,对基本蚁群算法中的信息素更新方法进行改进,提出了一种新的算法:基于特种蚁群优化算法,并将其用于信号盲检测。文中提出的改进蚁群算法能更好地避免优化算法出现过早停滞现象,优化盲检测性能。对改进算法的仿真实验及复杂度分析结果表明:基于特种蚁群优化盲检测算法在具有与原算法相同复杂度的前提下,提高了算法的盲检测性能,具有可行性和有效性。 Considering thedeficiencies about slow convergence and falling into local optimum easily in the processing of solution for standard ant colony algorithm, an improved ant colony algorithm, TACO,is presented to solve the defects and applied to blind signal de- tection. The new algorithm avoids premature stagnation and optimizes its performance. The experiment results of the improved algorithm and complexity analysis shows that under the premise of same complexity with the original algorithm,the TACO improves the performance of the blind detection,which is feasible and effective.
出处 《计算机技术与发展》 2013年第11期74-76,81,共4页 Computer Technology and Development
基金 国家自然科学基金资助项目(60772060) 南京邮电大学引进人才项目(NY212022) 南京邮电大学青蓝工程项目(NY210037)
关键词 特种蚁群优化算法 盲检测 收敛性 TACO blind detection convergence
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参考文献14

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