Godwin Shen

2010-03-21T18:42:46Z

Godwin:

== Godwin Shen ==

http://biron.usc.edu/~godwinsh/me.jpg

Ph.D. Candidate

Department of Electrical Engineering - Systems

University of Southern California

Los Angeles, CA

E-mail: godwinsh@usc.edu

Advisor: [http://sipi.usc.edu/~ortega Antonio Ortega]

== Research Interests ==
*Energy-Efficient Data Compression for Wireless Sensor Networks
*Image Compression
*Wavelet Transforms

== Education ==
*Sep. 2005-present: University of Southern California, Los Angeles, CA
**Ph.D. student, Department of Electrical Engineering-Systems
*Sep. 2005-May 2007: University of Southern California, Los Angeles, CA
**Master of Science in Electrical Engineering, May 2007, Department of Electrical Engineering-Systems
*Sep. 2001-Jun. 2005: California State Polytechnic University, Pomona
**Bachelor of Science in Electrical Engineering, Jun. 2005, Department of Electrical Engineering

== Professional Experience ==
*[http://jpl.nasa.gov Jet Propulsion Laboratory]: May 2008-Aug. 2008
**Intern in Information Processing Group
**Research in Distributed Data Compression

*[http://www.raytheon.com Raytheon]: May 2003-Aug. 2005
**Intern in Systems Engineering
**System Specification and Test for Air Defense Systems

== Fellowships / Awards ==
*USC Viterbi School of Engineering Doctoral Fellowship (Sep. 2005-May 2009)

*NASA Space Grant Award (May 2008-Aug. 2008)

*NASA Pair Grant Award (Sep. 2004-Jun. 2005)

== Skills / Tools ==
*Proficient in C/C++, MatLab.
*Working knowledge of Windows and UNIX systems.

== Publications ==
<ul>
<li> G. Shen and A. Ortega, "Transform-based Distributed Data Gathering". To Appear in IEEE Transactions on Signal Processing.
[http://arxiv.org/abs/0909.5177v3 arXiv:0909.5177v3]</ul>

<ul>
<li> S.K. Narang, G. Shen and A. Ortega, "Unidirectional Graph-based Wavelet Transforms for Efficient Data Gathering in Sensor Netowkrs". To Appear in 2010 IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP'10), Dallas, April 2010.</ul>

<ul>
<li> A. Sanchez, G. Shen and A. Ortega, "Edge-preserving Depth-map Coding Using Graph-based Wavelets". In Proc. of Asilomar 2009, Pacific Grove, October 2009.
[http://biron.usc.edu/~godwinsh/Papers/Asilomar.pdf PDF format]</ul>

<ul>
<li> P. Tarrio, G. Valenzise, G. Shen and A. Ortega, "Distributed Network Configuration for Wavelet-based Compression in Sensor Networks". In Proc. of Third Intl. Conf. on Geosensor Networks (GSN'09), Oxford, July 2009.
[http://biron.usc.edu/~godwinsh/Papers/GSN09.pdf PDF format]</ul>

<ul>
<li> G. Shen and A. Ortega, "Tree-Based Wavelets for Image Coding: Orthogonalization and Tree Selection". In Proc. of 2009 Picture Coding Symposium (PCS'09), Chicago, May 2009.
[http://biron.usc.edu/~godwinsh/Papers/PCS09.pdf PDF format]</ul>

<ul>
<li> G. Shen, S. Pattem and A. Ortega, "Energy-efficient Graph-based Wavelets for Distributed Coding in Wireless Sensor Networks". In Proc. of 2009 IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP'09), Taipei, April 2009.
[http://biron.usc.edu/~godwinsh/Papers/ICASSP09_Broadcast.pdf PDF format]</ul>

<ul>
<li> G. Shen, S. Narang and A. Ortega, "Adaptive Distributed Transforms for Irregularly Sampled Wireless Sensor Networks". In Proc. of 2009 IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP'09), Taipei, April 2009.
[http://biron.usc.edu/~godwinsh/Papers/ICASSP09_Filter_Opt.pdf PDF format]</ul>

<ul>
<li> S. Pattem, G. Shen, Y. Chen, B. Krishnamachari and A. Ortega, "SenZip: An Architecture for Distributed En-route Compression in Wireless Sensor Networks". In Workshop on Sensor Networks for Earth and Space Science Applications (ESSA'09), San Francisco, April 2009.
[http://biron.usc.edu/~godwinsh/Papers/ESSA09.pdf PDF format]</ul>

<ul>
<li> G. Shen and A. Ortega, "Compact Image Representation Using Wavelet Lifting Along Arbitrary Trees". In Proc. of 2008 IEEE Intl. Conf. on Image Processing (ICIP'08), San Diego, October 2008.
[http://biron.usc.edu/~godwinsh/Papers/ICIP08ShenOrtega.pdf PDF format]</ul>

<ul>
<li> G. Shen and A. Ortega, "Joint Routing and 2D Transform Optimization for Irregular Sensor Network Grids Using Wavelet Lifting". In Proc. of Fifth Intl. Conf. on Information Processing in Sensor Networks (IPSN'08), St. Louis, April 2008.
[http://biron.usc.edu/~godwinsh/Papers/IPSN08ShenOrtega.pdf PDF format]</ul>

<ul>
<li> G. Shen and A. Ortega, "Optimized Distributed 2D Transforms for Irregularly Sampled Sensor Network Grids Using Wavelet Lifting". In Proc. of 2008 IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP'08), Las Vegas, April 2008.
[http://biron.usc.edu/~godwinsh/Papers/ICASSP08ShenOrtega.pdf PDF format]</ul>

== Miscellaneous ==
<ul>
<li> G. Shen, S. Y. Lee, S. Lee, S. Pattem, A. Tu, B. Krishnamachari, A. Ortega, M. Cheng, S. Dolinar, A. Kiely, H. Xie, "Novel Distributed Wavelet Transforms and Routing Algorithms for Efficient Data Gathering in Sensor Webs". Earth Science and Tech. Conf. (ESTC'08), Adelphi, MD, June 2008.
[http://biron.usc.edu/~godwinsh/Papers/ESTC08.pdf PDF format]</ul>

<ul>
<li> S. Lee, S. Pattem, G. Shen, A. Tu, B. Krishnamachari, A. Ortega, M. Cheng, S. Dolinar, A. Kiely, H. Xie, "A Distributed Wavelet Approach for Efficient Information Representation and Data Gathering in Sensor Webs". NASA Science and Tech. Conf. (NSTC'07), Adelphi, MD, May 2007.
[http://biron.usc.edu/~godwinsh/Papers/NSTC07.pdf PDF format]</ul>

== Related Links ==
*[http://biron.usc.edu/wiki/index.php/CompressionGroup/DSNProject Distributed Compression for Sensor Networks]

*[http://biron.usc.edu/wiki/index.php?title=CompressionGroup Compression Research Group]

*[http://biron.usc.edu/wiki/index.php/Wavelets_on_Trees Source Code for Distributed Compression Algorithms]

Godwin Shen

2010-03-21T18:42:19Z

Godwin: /* Publications */

== Godwin Shen ==

http://biron.usc.edu/~godwinsh/me.jpg

Ph.D. Candidate

Department of Electrical Engineering - Systems

University of Southern California

Los Angeles, CA

E-mail: godwinsh@usc.edu

Advisor: [http://sipi.usc.edu/~ortega Antonio Ortega]

== Research Interests ==
*Energy-Efficient Data Compression for Wireless Sensor Networks
*Image Compression
*Wavelet Transforms

== Education ==
*Sep. 2005-present: University of Southern California, Los Angeles, CA
**Ph.D. student, Department of Electrical Engineering-Systems
*Sep. 2005-May 2007: University of Southern California, Los Angeles, CA
**Master of Science in Electrical Engineering, May 2007, Department of Electrical Engineering-Systems
*Sep. 2001-Jun. 2005: California State Polytechnic University, Pomona
**Bachelor of Science in Electrical Engineering, Jun. 2005, Department of Electrical Engineering

== Professional Experience ==
*[http://jpl.nasa.gov Jet Propulsion Laboratory]: May 2008-Aug. 2008
**Intern in Information Processing Group
**Research in Distributed Data Compression

*[http://www.raytheon.com Raytheon]: May 2003-Aug. 2005
**Intern in Systems Engineering
**System Specification and Test for Air Defense Systems

== Fellowships / Awards ==
*USC Viterbi School of Engineering Doctoral Fellowship (Sep. 2005-May 2009)

*NASA Space Grant Award (May 2008-Aug. 2008)

*NASA Pair Grant Award (Sep. 2004-Jun. 2005)

== Skills / Tools ==
*Proficient in C/C++, MatLab.
*Working knowledge of Windows and UNIX systems.

== Publications ==
<ul>
<li> G. Shen and A. Ortega, "Transform-based Distributed Data Gathering". To Appear in IEEE Transactions on Signal Processing.
[http://arxiv.org/abs/0909.5177v3 arXiv:0909.5177v3]</ul>

<ul>
<li> S.K. Narang, G. Shen and A. Ortega, "Unidirectional Graph-based Wavelet Transforms for Efficient Data Gathering in Sensor Netowkrs". To Appear in 2010 IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP'10), Dallas, April 2010.</ul>

<ul>
<li> A. Sanchez, G. Shen and A. Ortega, "Edge-preserving Depth-map Coding Using Graph-based Wavelets". In Proc. of Asilomar 2009, Pacific Grove, October 2009.
[http://biron.usc.edu/~godwinsh/Papers/Asilomar.pdf PDF format]</ul>

<ul>
<li> P. Tarrio, G. Valenzise, G. Shen and A. Ortega, "Distributed Network Configuration for Wavelet-based Compression in Sensor Networks". In Proc. of Third Intl. Conf. on Geosensor Networks (GSN'09), Oxford, July 2009.
[http://biron.usc.edu/~godwinsh/Papers/GSN09.pdf PDF format]</ul>

<ul>
<li> G. Shen and A. Ortega, "Tree-Based Wavelets for Image Coding: Orthogonalization and Tree Selection". In Proc. of 2009 Picture Coding Symposium (PCS'09), Chicago, May 2009.
[http://biron.usc.edu/~godwinsh/Papers/PCS09.pdf PDF format]</ul>

<ul>
<li> G. Shen, S. Pattem and A. Ortega, "Energy-efficient Graph-based Wavelets for Distributed Coding in Wireless Sensor Networks". In Proc. of 2009 IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP'09), Taipei, April 2009.
[http://biron.usc.edu/~godwinsh/Papers/ICASSP09_Broadcast.pdf PDF format]</ul>

<ul>
<li> G. Shen, S. Narang and A. Ortega, "Adaptive Distributed Transforms for Irregularly Sampled Wireless Sensor Networks". In Proc. of 2009 IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP'09), Taipei, April 2009.
[http://biron.usc.edu/~godwinsh/Papers/ICASSP09_Filter_Opt.pdf PDF format]</ul>

<ul>
<li> S. Pattem, G. Shen, Y. Chen, B. Krishnamachari and A. Ortega, "SenZip: An Architecture for Distributed En-route Compression in Wireless Sensor Networks". In Workshop on Sensor Networks for Earth and Space Science Applications (ESSA'09), San Francisco, April 2009.
[http://biron.usc.edu/~godwinsh/Papers/ESSA09.pdf PDF format]</ul>

<ul>
<li> G. Shen and A. Ortega, "Compact Image Representation Using Wavelet Lifting Along Arbitrary Trees". In Proc. of 2008 IEEE Intl. Conf. on Image Processing (ICIP'08), San Diego, October 2008.
[http://biron.usc.edu/~godwinsh/Papers/ICIP08ShenOrtega.pdf PDF format]</ul>

<ul>
<li> G. Shen and A. Ortega, "Joint Routing and 2D Transform Optimization for Irregular Sensor Network Grids Using Wavelet Lifting". In Proc. of Fifth Intl. Conf. on Information Processing in Sensor Networks (IPSN'08), St. Louis, April 2008.
[http://biron.usc.edu/~godwinsh/Papers/IPSN08ShenOrtega.pdf PDF format]</ul>

<ul>
<li> G. Shen and A. Ortega, "Optimized Distributed 2D Transforms for Irregularly Sampled Sensor Network Grids Using Wavelet Lifting". In Proc. of 2008 IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP'08), Las Vegas, April 2008.
[http://biron.usc.edu/~godwinsh/Papers/ICASSP08ShenOrtega.pdf PDF format]</ul>

== Miscellaneous ==
<ul>
<li> G. Shen, S. Y. Lee, S. Lee, S. Pattem, A. Tu, B. Krishnamachari, A. Ortega, M. Cheng, S. Dolinar, A. Kiely, H. Xie, "Novel Distributed Wavelet Transforms and Routing Algorithms for Efficient Data Gathering in Sensor Webs". Earth Science and Tech. Conf. (ESTC'08), Adelphi, MD, June 2008.
[http://biron.usc.edu/~godwinsh/Papers/ESTC08.pdf PDF format]</ul>

<ul>
<li> S. Lee, S. Pattem, G. Shen, A. Tu, B. Krishnamachari, A. Ortega, M. Cheng, S. Dolinar, A. Kiely, H. Xie, "A Distributed Wavelet Approach for Efficient Information Representation and Data Gathering in Sensor Webs". NASA Science and Tech. Conf. (NSTC'07), Adelphi, MD, May 2007.
[http://biron.usc.edu/~godwinsh/Papers/NSTC07.pdf PDF format]</ul>

== Related Links ==
*[http://biron.usc.edu/wiki/index.php/CompressionGroup/DSNProject Distributed Compression for Sensor Networks]

*[http://biron.usc.edu/wiki/index.php?title=CompressionGroup Compression Research Group]

*[http://biron.usc.edu/wiki/index.php/Wavelets_on_Trees Source Code for Distributed Compression Algorithms]

Wavelets on Trees

2010-02-25T00:52:33Z

Godwin:

2009-08-20T17:49:15Z

Godwin:

CompressionGroup/DSNProject

2009-08-20T17:47:44Z

Godwin:

Distributed Energy-Efficient Wavelet Compression Algorithms for Wireless Mutihop Sensor Networks


Low cost programmable sensors can be deployed in the environment to
perform a variety of coordinated tasks, such as object tracking,
environment monitoring/ surveillance and control. The
fast development and decreasing cost of wireless technologies have
made sensor networks a key technology for the future, and led to
substantial interest on distributed algorithms targeted at these
networks.



Assume that a number of power-constrained sensors are spr\-ead over an
area, acquiring data, e.g., temperature measurements. An estimate of
the temperature in each point of that area is to be made available at
a central node (sink) based on transmissions from the sensors. Each sensor is capable of transmitting data
only over a small distance. Communication is done via data hoping,
where data from each sensor is forwarded (using other sensors as relay
stations) until it reaches the target node. Such a network is referred
to as a multihop network.



A simple and naive design would be for each sensor to just transmit a
quantized version of its own measurement to the central node. However,
this approach would not be exploiting the fact that measurements
originated from spatially close sensors are likely to be correlated,
and energy would be wasted with the transmission of redundant data to
the central node. As an alternative, since data is correlated, it
would be reasonable to use some sort of transform as a means to
decorrelate the information from sensors, and, therefore, represent
the measurements using fewer bits.



Servetto and Gastpar have proposed the
use of distributed transforms to decorrelate data. A main drawback of
those algorithms is that in a power constrained sensor network
scenario, transmission costs account for most (if not all) the energy
consumption. Distributed algorithms that rely on a potentially large
number of intersensor communications, or do not take into account
communication costs as a function of the number of bits and the
distances over which bits are transmitted, might in the end be elevating power
consumption to unacceptable levels. For example, in the case of
distributed wavelet algorithms, the amount of necessary data exchanges
and the degree of decorrelation achieved are directly related to the
number of levels of decompositions used. Depending on the network
properties (data correlation, distances between sensors, etc), a
specific number of decompositions may perform better.



Distributed implementation of the wavelet transform poses several
challenges. First, if the filters contain anticausal terms,
sensors would be required to transmit data backwards (i.e., away from the
sink instead of towards the sink) or alternatively to send
uncompressed data forward. Second, any data transmitted back and
forth over the network has to be quantized, since tramsmissions at
full precision can substantialy increase energy consumption, affecting
the final performance. In this project we develop a distributed wavelet
transform algorithm to decorrelate data as it flows through the
network. We eliminate unnecessary transmissions by calculating partial
approximations of the wavelet coefficients based on the available data
at each sensor. The coefficients are refined at future nodes, as data
is forwarded to the sink. We also address the impact of data
quantization on the final distortion. We derive an upper bound to the
resulting extra distortion introduced by quantization in terms of the
bits allocated to the partial data, and use it as a tool to design the
quantizers so the extra distortion is within a given threshold.



We then address the scenario where energy-constrained sensors in a wireless sensor network can choose among different distributed

coding schemes to encode their data. We propose a framework where the network is described as a graph, with sensors representing

the nodes, and where communication and processing costs are associated to edge weights and the coding schemes associated to states

of operation. After carefully describing data transitions and edge costs, we show that a shor\-test-path algorithm can be used to

find the optimum network configuration, i.e., the one that leads to the lowest overall energy.



Our methods discussed above apply when the transform is performed along a single path (ergo, no overlapping paths). Naturally, this breaks down when applying this transform along more general routing trees that have overlapping paths.

To address this problem, we propose a wavelet transform that can be computed along an arbitrary routing tree using wavelet lifting. This eliminates the need for costly heuristics to merge overlapping 1D transforms. The transform is critically sampled, exploits data correlation across adjacent paths, and is computed in a unidirectional manner to avoid incurring additional costs for backward transmissions found in existing 2D transforms.

An optimization technique (analogous to that in our previous work) is then developed for our proposed tree based transform to select the number of levels of decomposition at each node that results in minimum cost.

We also propose a method for joint transform and routing optimization using our tree based transform to exploit a trade-off between high inter-node data correlation (for good compression efficiency) and low total distance to route to the sink (for low total routing cost).



More detailed information about this project can be found in the publications below.


 

Distributed compression algorithms for quantizer design, encoding of quantized data and source localization in sensor networks

In sensor networks, multiple correlated observations are available
from many sensors that can sense, compute and communicate. Often
these sensors are battery-powered and operate under strict
limitations on wireless communication bandwidth. This motivates
the use of data compression in the context of various tasks such
as detection, classification, localization and tracking, which
require data exchange between sensors. The basic strategy for
reducing the overall energy usage in the sensor network would then
be to decrease the communication cost at the expense of additional
computation in the sensors. One important sensor collaboration task with broad applications is source localization. Since practical systems will require
quantization of the observations before transmission, different
quantizer designs should be compared in terms of localization
error.


In the project, we consider the effect
of quantization on source localization and provide distributed
algorithms for quantizer design, encoding of quantized data and
localization based on them, to achieve good data compression.



More detailed information about this project can be found in the publications below.

 
<ul>

<li>'''Publications'''
<ul>

<li> S. Lee, S. Pattem, M. Sathiamoorthy,B. Krishnamachari, and A. Ortega "Spatially-Localized Compressed Sensing and Routing in Multi-hop Sensor Networks". In Proceedings of Third International Conference on Geosensor Networks (GSN'09), Oxford, July 2009.
[http://biron.usc.edu/~sungwonl/Papers/GSN09_CS.pdf PDF format]

<li> P. Tarrio, G. Valenzise, G. Shen and A. Ortega, "Distributed Network Configuration for Wavelet-based Compression in Sensor Networks". Third International Conference on Geosensor Networks (GSN'09), Oxford, Jul 2009.
[http://biron.usc.edu/~godwinsh/Papers/GSN09.pdf PDF format]

<li> G. Shen, S. Pattem and A. Ortega, "Energy-efficient Graph-based Wavelets for Distributed Coding in Wireless Sensor Networks". IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP'09), Taipei, Apr 2009.
[http://biron.usc.edu/~godwinsh/Papers/ICASSP09_Broadcast.pdf PDF format]

<li> G. Shen, S. Narang and A. Ortega, "Adaptive Distributed Transforms for Irregularly Sampled Wireless Sensor Networks". IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP'09), Taipei, Apr 2009.
[http://biron.usc.edu/~godwinsh/Papers/ICASSP09_Filter_Opt.pdf PDF format]

<li> S. Pattem, G. Shen, Y. Chen, B. Krishnamachari and A. Ortega, "SenZip: An Architecture for Distributed En-route Compression in Wireless Sensor Networks". In Workshop on Sensor Networks for Earth and Space Science Applications (ESSA'09), San Francisco, Apr 2009.
[http://biron.usc.edu/~godwinsh/Papers/ESSA09.pdf PDF format]

<li> G. Shen and A. Ortega, "Joint Routing and 2D Transform Optimization for Irregular Sensor Network Grids Using Wavelet Lifting". International Symposium on Information Processing in Sensor Networks (IPSN'08), St. Louis, Apr 2008.
[http://biron.usc.edu/~godwinsh/Papers/IPSN08ShenOrtega.pdf PDF format]

<li> G. Shen and A. Ortega, "Optimized Distributed 2D Transforms for Irregularly Sampled Sensor Network Grids Using Wavelet Lifting". IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP'08), Las Vegas, Apr 2008.
[http://biron.usc.edu/~godwinsh/Papers/ICASSP08ShenOrtega.pdf PDF format]

<li> A. Ciancio and A. Ortega, "Energy Efficient Data-Representation and Routing for
Wireless Sensor Networks Based on a Distributed
Wavelet Compression Algorithm". International Symposium on Information Processing in Sensor Networks (IPSN'06), Nashville, Apr 2006.
[http://biron.usc.edu/~godwinsh/Papers/IPSN06CiancioOrtega.pdf PDF format]

<li> A. Ciancio and A. Ortega, "A Dynamic Programming Approach to Distortion-Energy Optimization
for Distributed Wavelet Compression With Applications to
Data Gathering in Wireless Sensor Networks". IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP'06), Toulouse, France, May 2006.
[http://biron.usc.edu/~godwinsh/Papers/ICASSP06CiancioOrtega.pdf PDF format]

<li> Y. H. Kim and A. Ortega, "Maximum A Posteriori (MAP)-Based Algorithm for Distributed Source Localization using Quantized Acoustic Sensor Readings". IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP'06), Toulouse, France, May 2006.
[http://www-scf.usc.edu/~yhk/ICASSP06_yoon.pdf PDF format]

<li> A. Ciancio and A. Ortega, "Energy Consumption Optimization in
Wireless Sensor Networks Using Dynamic Programming (Work-in-progess)". International Symposium on Information Processing in Sensor Networks (IPSN'05), Los Angeles, Apr 2005.
[http://biron.usc.edu/~godwinsh/Papers/IPSN05CiancioOrtega.pdf PDF format]

<li> A. Ciancio and A. Ortega,"Distributed Wavelet
Compression Algorithm for Wireless Multihop Sensor Networks Based on Lifting". International Conference on Acoustics, Speech and Signal Processing (ICASSP'05), Philadelphia, Mar 2005.
[http://biron.usc.edu/~godwinsh/Papers/ICASSP05CiancioOrtega.pdf PDF format]

<li> Y. H. Kim and A. Ortega, "Quantizer Design for Source localization in Sensor Networks". IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP'05), Philadelphia, March 2005.
[http://www-scf.usc.edu/~yhk/ICASSP05_yoon.pdf PDF format]

<li> Y. H. Kim and A. Ortega, "Quantizer Design and Distributed Encoding Algorithm for Source Localization in Sensor Networks". International Symposium on Information Processing in Sensor Networks (IPSN'05), Los Angeles, April 2005.
[http://www-scf.usc.edu/~yhk/IPSN05_yoon.pdf PDF format]

<li> A. Ciancio and A. Ortega,"Distributed Wavelet Compression
Algorithm for Wireless Sensor Networks Based on Lifting", International Conference on Acoustics, Speech and Signal Processing (ICASSP'04), Montreal, May 2004.
[http://biron.usc.edu/~godwinsh/Papers/ICASSP04CiancioOrtega.pdf PDF format]

</ul>
 

<li>'''People'''
<ul>
<li> [http://sipi.usc.edu/~ortega/ Antonio Ortega]
<li> [http://biron.usc.edu/~ciancio/ Alexandre Ciancio]
<li> [http://www-scf.usc.edu/~yhk/ Yoon Hak Kim]
<li> [http://biron.usc.edu/~kumarsun/ Sunil Narang]
<li> [http://biron.usc.edu/wiki/index.php/Godwin Godwin Shen]
</ul>
 

<li>'''Related Links'''
<ul>
<li> [http://biron.usc.edu/wiki/index.php/Wavelets_on_Trees Wavelets on Trees]
<li> [http://anrg.usc.edu/SenZip/ SenZip] (developed jointly with the
[http://anrg.usc.edu/www/index.php/Main_Page USC Autonomous Networks Research Group, ANRG])

</ul>

Wavelets on Trees

2009-08-20T17:42:09Z

Godwin:

Wavelets on Trees

2009-08-20T17:41:03Z

Godwin:

Wavelets on Trees

2009-08-20T17:40:30Z

Godwin:

Wavelets on Trees

2009-08-20T17:39:51Z

Godwin:

Wavelets on Trees

2009-08-20T17:39:30Z

Godwin: