

Goals
Our main goal is to use mathematical and technological
knowledge to create new signal processing solutions
for important industrial and scientific problems.
We are interested in
 developing algorithms that are well suited to the
kind of hardware in which they will be employed 
generalpurpose computers, digital signal processors
(DSPs), or custom or semicustom hardware (FPGAs or
ASICS);
 deriving mathematical models to better understand
new and available algorithms, and to lay down the
path to the development of new and better methods.
Examples of tools and applications:
 Array processing: estimation of acoustic images
(maps of sound intensities) with microphone arrays.
 Adaptive filters: echo cancellation (cell phones),
system identification (control).
 Sparse identification methods: solving systems with
less equations than unknowns.
 Digital filters for samplerate conversion in audio
systems.
 Estimation and classification algorithms for
structural health monitoring (detection of defects in
mechanical structures).
Examples of mathematical tools frequently used: linear
algebra and matrix analysis, probability, statistics and
stochastic processes, transforms, and creativity.
Examples of hardware platforms: DSPs, FPGAs,
generalpurpose computers, GPAs.
Current research and development partnerships:
EMBRAER, University of York.
