EE 310 Seminar

Fely Barrera fely at gloworm.Stanford.EDU
Thu Jan 19 14:08:53 PST 2006

EE 310 Seminar
Date: Jan 24, 2006
Time: 4:15pm - 5:05 pm
Place: Hewlett 102

Title: Programmable and Reconfigurable Analog Signal Processing

Paul Hasler

ssociate Professor in the School of Electrical and Computer Engineering

Georgia Institute of Technology

With the need for low-power portable / autonomous sensor
systems, getting as much computation for a fixed power budget becomes more
and more critical. Analog signal processing can be a factor of 10,000 more
efficient, that is power dissipated for given computation bandwidth, than
custom digital computation for low to moderate (i.e. 6-12 bit SNR)
resolution signals. For these techniques to be viable, these analog
techniques must be programmable, and must scale in performance similar or
better than digital processing for smaller geometry devices. Analog
programmability will also have an impact on the resulting digital signal
processing circuits. Further, the potential of large-scale Field
Programmable Analog Arrays (FPAA), devices analogous to FPGAs with millions
of programmable analog parameters, opens up possibilities for a wide range
of applications, and the potential of widely available FPAA ICs makes these
approachable for a wide range of applications. Using these analog signal
processing techniques for a system design, signal compression is not only
essential for efficient transmission from the sensor, but for efficient
digital transmission between the ICs for low-power operation.

Paul Hasler is an Associate Professor in the School of Electrical and
Computer Engineering at Georgia Institute of Technology. Dr. Hasler
received his M.S. and B.S.E. in Electrical Engineering from Arizona State
University in 1991, and received his Ph.D. From California Institute of
Technology in Computation and Neural Systems in 1997. His current research
interests include low power electronics, mixed-signal system ICs,
floating-gate MOS transistors, adaptive information processing systems,
"smart" interfaces for sensors, cooperative analog-digital signal
processing, device physics related to submicron devices or floating-gate
devices, and analog VLSI models of on-chip learning and sensory processing
in neurobiology. Dr. Hasler received the NSF CAREER Award in 2001, and the
ONR YIP award in 2002. Dr. Hasler received the Paul Raphorst Best Paper
Award, IEEE Electron Devices Society, 1997, Best Paper at CICC 2005, Best
Sensors paper at ISCAS 2005, a Best paper award at SCI 2001. Dr. Hasler is a
Senior Member of the IEEE.

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