Research Assistantships at University of Colorado at Boulder

[Brown Tim]

It's not too late to apply. 

               University of Colorado at Boulder
                
The Department of Electrical and Computer Engineering at CU Boulder has
one and possibly more graduate research assistantships available for
work in the following areas:

-------- Adaptive Control of Broadband Communication Networks --------
Modern data traffic sources are characterized by many challenging
features from a network control standpoint:  difficult to model and
analyze queueing properties; inter-source correlations; slowly varying
statistical properties; diverse heterogeneous source types; misspec-
ified traffic descriptors; and inadvertent network traffic shaping.

We seek to address problems such as resource allocation, routing,
provisioning, and network design for such traffic using methods based
on statistical classification techniques that use historical data as to
what were acceptable combinations of carried traffic and what were not.

Technical problems range from efficient representation and storage of
historical data; choice and modification strategy of classifier model;
noise on the data; confidence intervals on decisions; directed and
undirected exploration of the decision space; filtering out
uninformative data; and implementations.

-------- Low-Power Neural Network Architectures for Wireless --------
Analog neural networks have demonstrated signal processing power
dissipations orders of magnitude less than comparable digital
implementations. This is promising for battery limited mobile and
wireless applications. Key to harnessing this potential is overcoming
noise, dynamic range, and precision limitations inherent to the analog
processing.

We seek to improve the scope and robustness of neural algorithms and
architectures including: techniques for mapping software neural
solutions into non-ideal hardware; robust algorithms for learning
directly in hardware; and developing neural design methodologies beyond
Hopfield energy functions for optimization problems. Research will be
guided by mobile signal processing applications such as equalization,
vector quantization, and adaptive filtering.

Opportunities exist for research in algorithms, architectures, and also
hardware implementations.

  -------- Design Optimization for Low Power Communication --------
Communication systems are designed by separately optimizing components
such as RF front ends, error correcting codes, and diversity
strategies. The goals of the individual designs (such as designing for
capacity in error correcting codes) may not always match the global
objective and this approach ignores the coupling between design choices
in each module. Simple yet non-intuitive examples show that dramatic
power reductions are possible with a holistic design.

We seek to address this at two levels. As a static design problem,
formulating the problem as an objective function is conceptually
straight forward, but due to a wide variety of continuous/discrete,
linear/non-linear, and deterministic/stochastic constraints and
variables requires conventional techniques need to be supplemented by
more robust methods such as genetic algorithms.  At a dynamic level the
communication design is not required to be static and flexible DSP
hardware allows for different strategies to be tried as a function of
the current communication environment (e.g. power control).

Technical problems range from formalizing a design problem that crosses
many research domains; optimization over multiple variable types; and
methods for making decisions with uncertainty and incomplete knowledge
in dynamic environments.

For more info contact Prof. Tim Brown, timxb at colorado.edu (303) 492-1630