For almost five decades, DSPG in RLE has
been at the forefront of the exciting field of Signal Processing.
Our current focus is on
the development of signal processing algorithms with the view that
signal processing is a technology which spans a host of application
areas. While the development of meaningful and potentially
useful algorithms is done best with attention to potential applications,
the commitment in our current research is to the algorithms in general
rather than to specific applications. Consistently, our group
has successfully looked to application areas such as speech and
image processing, sensor networks, communications, and radar and
sonar, to name a few.
Much of our research over
the years has been involved in the development of algorithms in
traditional areas such as signal modelling, quantization, parameter
estimation, sampling and signal representations. We have also
successfully explored unconventional directions such as algorithms
based on fractal signals, chaotic behavior in nonlinear dynamical
systems, and the exploitation of solitons associated with particular
classes of nonlinear wave equations. These creative directions
can be categorized–at least initially–as "solutions
in search of problems". However, quite typically we have
been able to eventually identify potential applications for these
solutions. In many cases, these unique projects have led
to patents and have been incorporated into real world systems.
Another approach we have taken in developing
new algorithms has been to look to nature for inspiration and as
a metaphor for new signal processing directions. Our work on chaos,
solitons and fractals falls in this category to a certain extent.
More recently, studying quantum mechanics as a parallel has led
us to the development of a variety of new algorithmic frameworks,
which we describe as Quantum Signal Processing (QSP). In a
similar vein, we are studying signal processing in cell biology
and its potential as an analogy for new signal processing algorithms.
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