A Hybrid Seachr Architecture Applied to Hard Random 3-SAT and Low-Autocorrelation Binary Sequences
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
Finding low autocorrelation binary sequences with memetic algorithms
Applied Soft Computing
Advances in the merit factor problem for binary sequences
Journal of Combinatorial Theory Series A
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The value2e^{2}is calculated by approximations as a conjectured asymptotic limit for the best central to sidelobe energy ratio of very long low autocorrelation binary sequences. The same bound is calculated by approximation for skewsymmetric sequences, hence it is concluded that the requirement of skewsymmetry constitutes a powerful and effective sieve for the search for near-optimal sequences. A second sieve based on the use of complementary sequences is discussed and shown to be quite effective for sequence lengths up to 31, and its investigation for longer lengths by means of computers is suggested. A third and a fourth sieve, based on the selection of restricted classes of complementary sequences, are also discussed.