5,101 research outputs found
New Optimal Binary Sequences with Period via Interleaving Ding-Helleseth-Lam Sequences
Binary sequences with optimal autocorrelation play important roles in radar,
communication, and cryptography. Finding new binary sequences with optimal
autocorrelation has been an interesting research topic in sequence design.
Ding-Helleseth-Lam sequences are such a class of binary sequences of period
, where is an odd prime with . The objective of this
letter is to present a construction of binary sequences of period via
interleaving four suitable Ding-Helleseth-Lam sequences. This construction
generates new binary sequences with optimal autocorrelation which can not be
produced by earlier ones
Convolutional compressed sensing using deterministic sequences
This is the author's accepted manuscript (with working title "Semi-universal convolutional compressed sensing using (nearly) perfect sequences"). The final published article is available from the link below. Copyright @ 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.In this paper, a new class of orthogonal circulant matrices built from deterministic sequences is proposed for convolution-based compressed sensing (CS). In contrast to random convolution, the coefficients of the underlying filter are given by the discrete Fourier transform of a deterministic sequence with good autocorrelation. Both uniform recovery and non-uniform recovery of sparse signals are investigated, based on the coherence parameter of the proposed sensing matrices. Many examples of the sequences are investigated, particularly the Frank-Zadoff-Chu (FZC) sequence, the m-sequence and the Golay sequence. A salient feature of the proposed sensing matrices is that they can not only handle sparse signals in the time domain, but also those in the frequency and/or or discrete-cosine transform (DCT) domain
Source-independent quantum random number generation
Quantum random number generators can provide genuine randomness by appealing
to the fundamental principles of quantum mechanics. In general, a physical
generator contains two parts---a randomness source and its readout. The source
is essential to the quality of the resulting random numbers; hence, it needs to
be carefully calibrated and modeled to achieve information-theoretical provable
randomness. However, in practice, the source is a complicated physical system,
such as a light source or an atomic ensemble, and any deviations in the
real-life implementation from the theoretical model may affect the randomness
of the output. To close this gap, we propose a source-independent scheme for
quantum random number generation in which output randomness can be certified,
even when the source is uncharacterized and untrusted. In our randomness
analysis, we make no assumptions about the dimension of the source. For
instance, multiphoton emissions are allowed in optical implementations. Our
analysis takes into account the finite-key effect with the composable security
definition. In the limit of large data size, the length of the input random
seed is exponentially small compared to that of the output random bit. In
addition, by modifying a quantum key distribution system, we experimentally
demonstrate our scheme and achieve a randomness generation rate of over
bit/s.Comment: 11 pages, 7 figure
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