1,435 research outputs found
Phase space polarization and the topological string: a case study
We review and elaborate on our discussion in hep-th/0606112 on the interplay
between the target space and the worldsheet description of the open topological
string partition function, for the example of the conifold. We discuss the
appropriate phase space and canonical form for the system. We find a map
between choices of polarization and the worldsheet description, based on which
we study the behavior of the partition function under canonical
transformations.Comment: 18 pages, invited review for MPL
Sequential joint signal detection and signal-to-noise ratio estimation
The sequential analysis of the problem of joint signal detection and
signal-to-noise ratio (SNR) estimation for a linear Gaussian observation model
is considered. The problem is posed as an optimization setup where the goal is
to minimize the number of samples required to achieve the desired (i) type I
and type II error probabilities and (ii) mean squared error performance. This
optimization problem is reduced to a more tractable formulation by transforming
the observed signal and noise sequences to a single sequence of Bernoulli
random variables; joint detection and estimation is then performed on the
Bernoulli sequence. This transformation renders the problem easily solvable,
and results in a computationally simpler sufficient statistic compared to the
one based on the (untransformed) observation sequences. Experimental results
demonstrate the advantages of the proposed method, making it feasible for
applications having strict constraints on data storage and computation.Comment: 5 pages, Proceedings of IEEE International Conference on Acoustics,
Speech, and Signal Processing (ICASSP), 201
Relaying Simultaneous Multicast Messages
The problem of multicasting multiple messages with the help of a relay, which
may also have an independent message of its own to multicast, is considered. As
a first step to address this general model, referred to as the compound
multiple access channel with a relay (cMACr), the capacity region of the
multiple access channel with a "cognitive" relay is characterized, including
the cases of partial and rate-limited cognition. Achievable rate regions for
the cMACr model are then presented based on decode-and-forward (DF) and
compress-and-forward (CF) relaying strategies. Moreover, an outer bound is
derived for the special case in which each transmitter has a direct link to one
of the receivers while the connection to the other receiver is enabled only
through the relay terminal. Numerical results for the Gaussian channel are also
provided.Comment: This paper was presented at the IEEE Information Theory Workshop,
Volos, Greece, June 200
Measurement Matrix Design for Compressive Sensing Based MIMO Radar
In colocated multiple-input multiple-output (MIMO) radar using compressive
sensing (CS), a receive node compresses its received signal via a linear
transformation, referred to as measurement matrix. The samples are subsequently
forwarded to a fusion center, where an L1-optimization problem is formulated
and solved for target information. CS-based MIMO radar exploits the target
sparsity in the angle-Doppler-range space and thus achieves the high
localization performance of traditional MIMO radar but with many fewer
measurements. The measurement matrix is vital for CS recovery performance. This
paper considers the design of measurement matrices that achieve an optimality
criterion that depends on the coherence of the sensing matrix (CSM) and/or
signal-to-interference ratio (SIR). The first approach minimizes a performance
penalty that is a linear combination of CSM and the inverse SIR. The second one
imposes a structure on the measurement matrix and determines the parameters
involved so that the SIR is enhanced. Depending on the transmit waveforms, the
second approach can significantly improve SIR, while maintaining CSM comparable
to that of the Gaussian random measurement matrix (GRMM). Simulations indicate
that the proposed measurement matrices can improve detection accuracy as
compared to a GRMM
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