Title :
New binary sequences with good aperiodic autocorrelations obtained by evolutionary algorithm
Author :
Deng, Xinmin ; Fan, Pingzhi
Author_Institution :
Inst. of Mobile Commun., Southwest Jiaotong Univ., Chengdu, China
Abstract :
A new binary sequences for lengths up to 100 with good autocorrelation function properties are presented. The results obtained by an evolutionary algorithm are better than other known results in most cases.
Keywords :
binary sequences; correlation methods; evolutionary computation; aperiodic autocorrelations; autocorrelation function properties; binary sequence lengths; binary sequences; evolutionary algorithm; optimization; Application software; Autocorrelation; Binary sequences; Energy measurement; Evolution (biology); Evolutionary computation; Length measurement; Neural networks; Optimization methods; Radar applications;
Journal_Title :
Communications Letters, IEEE
DOI :
10.1109/4234.798020
