2006
DOI: 10.1017/s0963548306007589
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Autocorrelations of Random Binary Sequences

Abstract: We define B n to be the set of n-tuples of the form (a 0 , . . . , a n−1 ) where a j = ±1. If A ∈ B n , then we call A a binary sequence and define the autocorrelations of A by c k := n−k−1 j=0 a j a j+k for 0 k n − 1. The problem of finding binary sequences with autocorrelations 'near zero' has arisen in communications engineering and is also relevant to conjectures of Littlewood and Erdős on 'flat' polynomials with ±1 coefficients. Following Turyn, we define b(n) := min A∈Bn max 1 k n−1 |c k |.The purpose of… Show more

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Cited by 27 publications
(20 citation statements)
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“…This stance is in contrast to many of those seen in the quest for low correlated binary sequences [2], [3] with no follow-up filtering. The MPS codes explicitly evaluate the code ACF and the sidelobes encountered; this search, though burdensome, is the most dependable course of action.…”
Section: Our Policy On Code Selectioncontrasting
confidence: 74%
See 1 more Smart Citation
“…This stance is in contrast to many of those seen in the quest for low correlated binary sequences [2], [3] with no follow-up filtering. The MPS codes explicitly evaluate the code ACF and the sidelobes encountered; this search, though burdensome, is the most dependable course of action.…”
Section: Our Policy On Code Selectioncontrasting
confidence: 74%
“…Barker codes (which exist only for length N=13 and some smaller values) all have 20 log 10 (1/N) as their peak sidelobe level while non-Barker codes have higher values (and, hence, more prominent false target replicas at the output of their matched filters), only decreasing (non-monotonically) agonizingly slowly with N [3]. The search space is enormous, requiring 2 N evaluations for each chosen code length, so it is no trivial matter to examine and assess large codes.…”
Section: Introductionmentioning
confidence: 99%
“…Apparently the suggested approach also allows proving that this bound is indeed true for most of the sequences (see comments at the bottom of p.670 in [18]). Dmitriev and Jedwab [4] conjectured and provided an experimental evidence that the typical PSL behaves as Θ( √ n ln n).…”
mentioning
confidence: 89%
“…Moon and Moser [19] proved that for almost all sequences, κ(n) ≤ M (S n ) ≤ (2 + ) √ n ln n, for any κ(n) = o( √ n). Mercer [18] showed that…”
mentioning
confidence: 99%
“…(It is clear from Theorem 1 (i) that for any fixed > 0, M n ≤ (2 + ) √ n log n when n is sufficiently large. The constant in this latter bound was improved from 2 to √ 2 by Mercer [8], but his proof applies only to M n and not to almost all binary sequences. )…”
Section: The Growth Rate Of the Psl Of Randomly-selected Binary Sequementioning
confidence: 99%