confpubs.bib
@inproceedings{simoni.99,
author = {Simoni, M. and Broening, B. and Rozell, C. and Meek, C. and Wakefield, G.},
title = {A theoretical framework for electro-acoustic music},
booktitle = {{International Computer Music Conference (ICMC)}},
year = {1999},
address = {Beijing, China},
url = {http://users.ece.gatech.edu/~crozell/pubs/simoniICMC1999.pdf}
}
@inproceedings{rozell.04b,
author = {Rozell, C.J. and Manolakis, D.},
title = {Matched filter performance for unequal target and background covariance matrices},
booktitle = {Proceedings of the SPIE Defense and Security Symposium: Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X},
year = {2004},
address = {Orlando, FL},
month = {April},
pages = {109--117},
abstract = {Detection of military and civilian targets from
airborne platforms using hyperspectral imaging (HSI) sensors is of
great interest. Relative to multispectral sensing, hyperspectral
sensing can increase the detectability of targets by exploiting finer
detail in spectral signatures. A multitude of adaptive detection
algorithms have appeared in the literature or have found their way into
software packages and end-user systems. The most widely known among them
is the linear matched filter. However, despite its popularity, the
fact that the matched filter is used under conditions that deviate
from the implicit optimality assumptions has not been investigated.}
}
@inproceedings{lexa.04,
author = {Lexa, M.A. and Rozell, C.J. and Sinanovi{\'c}, S. and Johnson, D.H.},
title = {To cooperate or not to cooperate: Detection strategies in sensor networks},
booktitle = {{Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP)}},
year = {2004},
address = {Montreal, Canada},
month = {May},
pages = {841--844},
abstract = {This paper is an initial investigation into the following
question: Can cooperation among sensors in a sensor network improve
detection performance in a simple hypothesis test? We analyze a simple
cooperative system using the Kullback-Leibler (KL) discrimination distance
and a quantity known as the information transfer ratio which is a
ratio of KL distances. We discover that, asymptotically, gain over a
non-cooperative system depends on the conditional KL distance. We conclude
with an illustrative example which demonstrates that cooperation not
only significantly improves performance but can also degrade it.},
url = {http://users.ece.gatech.edu/~crozell/pubs/lexaICASSP2004.pdf}
}
@inproceedings{rozell.04d,
author = {Rozell, C.J. and Johnson, D.H.},
title = {Analysis of noise reduction in redundant expansions under distributed processing requirements},
booktitle = {{Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP)}},
year = {2005},
address = {Philadelphia, PA},
month = {March},
pages = {185--188},
abstract = {We considered signal reconstruction with
redundant expansions under distributed processing in noisy environments.
Redundant expansions have the ability to reduce noise corrupting the
coefficients, but distributed processing schemes will not be able
to take full advantage of the redundancy present. We apply frame
theory and a generalization called ``frames of subspaces'' to find
conditions when distributed reconstruction suffers no loss in noise
reduction ability, and we bound performance loss in more general cases.},
url = {http://users.ece.gatech.edu/~crozell/pubs/rozellICASSP2005.pdf}
}
@inproceedings{rozell.05b,
author = {Rozell, C.J. and Goodman, I.N. and Johnson, D.H.},
title = {Feature-based information processing with selective attention},
booktitle = {{Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP)}},
year = {2006},
address = {Toulouse, France},
month = {May},
abstract = {We present a simple but general model for feature-based
information processing with selective attention. We model
feature extraction as projections onto frames of subspaces,
which accounts for redundancies in the representations of
individual features as well as between features. To manage
limited resources, we use feedback attentional signals to
dynamically allocate system resources according to the
observed events. In our model, attention maximizes the
average information retained about all events weighted by
their relative priorities. We illustrate the model with a
simple system under a total bit constraint and discuss how
the organization of the feature extraction affects the
optimal bit allocation.},
url = {http://users.ece.gatech.edu/~crozell/pubs/rozellICASSP2006.pdf}
}
@article{rozell.06,
author = {Rozell, C.J. and Johnson, D.H.},
title = {Evaluating local contributions to global performance in wireless sensor and actuator networks},
journal = {Lecture Notes in Computer Science},
year = 2006,
volume = 4026,
month = {June},
pages = {1--16},
note = {{\it Proceedings of the International Conference on Distributed Computing in Sensor Systems (DCOSS)}, San Francisco, CA, June 2006},
abstract = {Wireless sensor networks are often studied with the goal of removing
information from the network as efficiently as possible. However,
when the application also includes an actuator network, it is
advantageous to determine actions in-network. In such settings,
optimizing the sensor node behavior with respect to sensor information
fidelity does not necessarily translate into optimum behavior in terms
of action fidelity. Inspired by neural systems, we present a model of
a sensor and actuator network based on the vector space tools of
frame theory that applies to applications analogous to reflex
behaviors in biological systems. Our analysis yields bounds on both
absolute and average actuation error that point directly to strategies
for limiting sensor communication based not only on local measurements
but also on a measure of how important each sensor-actuator link is to
the fidelity of the total actuation output.},
url = {http://users.ece.gatech.edu/~crozell/pubs/rozellDCOSS2006.pdf}
}
@inproceedings{rozell.06b,
author = {Rozell, C.J. and Johnson, D.H.},
title = {Power Scheduling for Wireless Sensor and Actuator Networks},
booktitle = {Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN) },
year = 2007,
address = {Cambridge, MA},
month = {April},
pages = {470--478},
abstract = {We previously presented a model for some wireless sensor and actuator
network (WSAN) applications based on the vector space tools of frame
theory. In this WSAN model there is a weight associated to each
sensor-actuator link denoting the importance of that communication
link to the actuation fidelity. These weights were shown to be useful
in pruning away communication links to reduce the number of active
channels. Inspired by recent work in power scheduling for
decentralized estimation, we investigate the optimal allocation of
system resources for achieving a desired actuation fidelity. In this
scheme, each sensor acquires a noisy observation and sends a message
to a subset of actuators using an MQAM transmission strategy. The
message sent on each sensor-actuator communication link is quantized
with a variable number of bits, with the number of bits optimized to
minimize the total network power consumption subject to a constraint
on the actuation distortion. We show analytically and verify through
simulation that performing this optimal power scheduling can yield
significant power savings over communication strategies that use a
fixed number of bits on each communication link.},
url = {http://users.ece.gatech.edu/~crozell/pubs/rozellIPSN2007.pdf}
}
@inproceedings{casazza.07,
author = {Casazza, P. and Kutyniok, G. and Li, S. and Rozell, C.J.},
title = {Modeling sensor networks with fusion frames},
booktitle = {Proceedings of SPIE, Wavelets XII at SPIE Optics and Photonics},
volume = {6701},
year = 2007,
address = {San Diego, CA},
month = {August},
pages = {67011M-1 -- 67011M-11},
abstract = {The new notion of fusion frames will be presented in
this article. Fusion frames provide an extensive
framework not only to model sensor networks, but
also to serve as a means to improve robustness or
develop efficient and feasible reconstruction
algorithms. Fusion frames can be regarded as sets of
redundant subspaces each of which contains a
spanning set of local frame vectors, where the
subspaces have to satisfy special overlapping
properties. Main aspects of the theory of fusion
frames will be presented with a particular focus on
the design of sensor networks. New results on the
construction of Parseval fusion frames will also be
discussed.},
url = {http://users.ece.gatech.edu/~crozell/pubs/casazzaSPIE2007.pdf}
}
@inproceedings{rozell.07c,
author = {Rozell, C.J. and Johnson, D.H. and Baraniuk, R.G. and Olshausen, B.A.},
title = {Locally competitive algorithms for sparse approximation},
booktitle = {Proceedings of the International Conference on Image Processing (ICIP)},
year = 2007,
pages = {169--172},
address = {San Antonio, TX},
month = {September}
}
@inproceedings{ortman.08,
author = {Ortman, R.L. and Rozell, C.J. and Johnson, D.H.},
title = {Reconstruction of compressively sensed images via neurally plausible local competitive algorithms},
booktitle = {Proceedings of the Conference on Information Sciences and Systems (CISS)},
year = 2008,
address = {Princeton, NJ},
pages = {476--479},
month = {March}
}
@inproceedings{wakin.10,
author = {Wakin, M.B. and Park, J.Y. and \studfont{Yap}, \studfont{H.L.} and Rozell, C.J.},
title = {Concentration of Measure for Block Diagonal Measurement Matrices},
booktitle = {{Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP)}},
year = 2010,
month = {March},
address = {Dallas, TX},
abstract = {Concentration of measure inequalities are at the heart of much
theoretical analysis of randomized compressive operators. Though
commonly studied for dense matrices, in this paper we derive a
concentration of measure bound for block diagonal matrices where the
nonzero entries along the main diagonal blocks are i.i.d.
subgaussian random variables. Our main result states that the
concentration exponent, in the best case, scales as that for a fully
dense matrix. We also identify the role that the energy distribution
of the signal plays in distinguishing the best case from the worst.
We illustrate these phenomena with a series of experiments.},
url = {http://users.ece.gatech.edu/~crozell/pubs/wakinICASSP2010.pdf}
}
@inproceedings{halas.06,
author = {Bishnoi,S.W. and Levin,C.S. and Rozell,C.J. and Johnson,B.R. and Johnson,D.H. and Halas, N.J},
title = {All-optical nanoscale {pH} meter: a plasmonic nanodevice with quantifiable output},
booktitle = {Proceedings of the Annual Meeting of the {IEEE} Lasers and Electro-Optics Society (IEEE LEOS)},
year = 2006,
address = {Montreal, Canada},
month = {October},
note = {Invited paper}
}
@inproceedings{rozell.08b,
author = {Rozell, C.J.},
title = {Distributed processing in frames for sparse approximation},
booktitle = {Proceedings of the Conference on Information Sciences and Systems (CISS)},
year = 2008,
address = {Princeton, NJ},
month = {March},
note = {Invited paper},
abstract = {Beyond signal processing applications, frames are also powerful tools
for modeling the sensing and information processing of many biological
and man-made systems that exhibit inherent redundancy. In many cases,
these systems are required to use distributed computational strategies
to analyze and process the sensory information. In this talk, I will
review the use of frames to model distributed sensing systems with a
particular focus on sensory neural systems. In light of the evidence
that many of these systems employ sparse codes, I will describe our
Locally Competitive Algorithms (LCAs) that use a dynamical system to
solve many sparse approximation problems. These LCAs employ a
parallel computational architecture with simple analog components. I
will show numerical simulation results for these systems and describe
their relationship to the many recently-proposed iterative
thresholding algorithms. Our LCA approach also demonstrates potential
advantages in coding time-varying signals (e.g., video) by reflecting
the smooth signal changes in smooth coefficient variations. Finally, I
will highlight some future directions where we hope to impact areas
such as efficient analog signal processing devices, fast discrete
approximation algorithms, and video processing and computer vision in
complex temporal environments.},
url = {http://users.ece.gatech.edu/~crozell/pubs/rozellCISS2008.pdf}
}
@inproceedings{rozell.10,
author = {Rozell, C.J. and \studfont{Yap}, \studfont{H.L.} and Park, J.Y. and Wakin, M.B.},
title = {Concentration of Measure for Block Diagonal Matrices With Repeated Blocks},
booktitle = {Proceedings of the Conference on Information Sciences and Systems (CISS)},
year = 2010,
address = {Princeton, NJ},
month = {March},
note = {Invited paper},
abstract = {The theoretical analysis of randomized compressive operators often relies on the existence of a concentration of measure inequality for the operator of interest. Though commonly studied for unstructured, dense matrices, matrices with more structure are often of interest because they model constraints on the sensing system or allow more efficient system implementations. In this paper we derive a concentration of measure bound for block diagonal matrices where the nonzero entries along the main diagonal are a single repeated block of i.i.d. Gaussian random variables. Our main result states that the concentration exponent, in the best case, scales as that for a fully dense matrix. We also identify the role that the signal diversity plays in distinguishing the best and worst cases. Finally, we illustrate these phenomena with a series of experiments.},
url = {http://users.ece.gatech.edu/~crozell/pubs/rozellCISS2010.pdf}
}