360 research outputs found
Low-complexity dominance-based Sphere Decoder for MIMO Systems
The sphere decoder (SD) is an attractive low-complexity alternative to
maximum likelihood (ML) detection in a variety of communication systems. It is
also employed in multiple-input multiple-output (MIMO) systems where the
computational complexity of the optimum detector grows exponentially with the
number of transmit antennas. We propose an enhanced version of the SD based on
an additional cost function derived from conditions on worst case interference,
that we call dominance conditions. The proposed detector, the king sphere
decoder (KSD), has a computational complexity that results to be not larger
than the complexity of the sphere decoder and numerical simulations show that
the complexity reduction is usually quite significant
Group Frames with Few Distinct Inner Products and Low Coherence
Frame theory has been a popular subject in the design of structured signals
and codes in recent years, with applications ranging from the design of
measurement matrices in compressive sensing, to spherical codes for data
compression and data transmission, to spacetime codes for MIMO communications,
and to measurement operators in quantum sensing. High-performance codes usually
arise from designing frames whose elements have mutually low coherence.
Building off the original "group frame" design of Slepian which has since been
elaborated in the works of Vale and Waldron, we present several new frame
constructions based on cyclic and generalized dihedral groups. Slepian's
original construction was based on the premise that group structure allows one
to reduce the number of distinct inner pairwise inner products in a frame with
elements from to . All of our constructions further
utilize the group structure to produce tight frames with even fewer distinct
inner product values between the frame elements. When is prime, for
example, we use cyclic groups to construct -dimensional frame vectors with
at most distinct inner products. We use this behavior to bound
the coherence of our frames via arguments based on the frame potential, and
derive even tighter bounds from combinatorial and algebraic arguments using the
group structure alone. In certain cases, we recover well-known Welch bound
achieving frames. In cases where the Welch bound has not been achieved, and is
not known to be achievable, we obtain frames with close to Welch bound
performance
Artificial Intelligence Approach to the Determination of Physical Properties of Eclipsing Binaries. I. The EBAI Project
Achieving maximum scientific results from the overwhelming volume of
astronomical data to be acquired over the next few decades will demand novel,
fully automatic methods of data analysis. Artificial intelligence approaches
hold great promise in contributing to this goal. Here we apply neural network
learning technology to the specific domain of eclipsing binary (EB) stars, of
which only some hundreds have been rigorously analyzed, but whose numbers will
reach millions in a decade. Well-analyzed EBs are a prime source of
astrophysical information whose growth rate is at present limited by the need
for human interaction with each EB data-set, principally in determining a
starting solution for subsequent rigorous analysis. We describe the artificial
neural network (ANN) approach which is able to surmount this human bottleneck
and permit EB-based astrophysical information to keep pace with future data
rates. The ANN, following training on a sample of 33,235 model light curves,
outputs a set of approximate model parameters (T2/T1, (R1+R2)/a, e sin(omega),
e cos(omega), and sin i) for each input light curve data-set. The whole sample
is processed in just a few seconds on a single 2GHz CPU. The obtained
parameters can then be readily passed to sophisticated modeling engines. We
also describe a novel method polyfit for pre-processing observational light
curves before inputting their data to the ANN and present the results and
analysis of testing the approach on synthetic data and on real data including
fifty binaries from the Catalog and Atlas of Eclipsing Binaries (CALEB)
database and 2580 light curves from OGLE survey data. [abridged]Comment: 52 pages, accepted to Ap
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