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October 21, 2012

Mtg: Applications of Extreme Value Theory to Signal Processing

by @ 1:32 pm. Filed under ALL, Communications
 

FRIDAY October 26, 2012
SCV Computational Intelligence, with Signal Processing, Circuits & Systems, Robotics & Automation
Subject:
Speaker: Dr. Adam Rowell, Stanford University
Time: Presentation at 7:00 PM
Cost: none
Place: Packard 101, Stanford University, 350 Serra Mall, Stanford
RSVP: from website
Web: ewh.ieee.org/r6/scv/cis

Extreme value theory (EVT) is the study of the statistics of the extreme outliers in a random process.? It is especially useful for estimating probabilities of an extreme event when little or no past data has been recorded at a similar level.? Canonical examples of its application include predicting annual maximum river or wave heights and estimating worst-case insurance or stock market losses.? Many problems in electrical engineering can benefit from the application of EVT, though such research is just getting started.? In this talk, we will go over the basics of extreme value theory and show how its principles are useful to a few signal processing applications.
Both examples we investigate will illustrate how existing problems in electrical engineering can be easily tackled using EVT, yielding useful models.? For the first application, we investigate the effects of quantization on digital filter performance.? When digital filter coefficients are quantized, as is common in high-speed or low-power hardware, the performance can be significantly degraded.? We will start with a quick overview of simple digital filters and their frequency response, and will see the effects of quantization on performance.? Extreme value theory will then be applied to the frequency response of the quantized filter to model how the quantization affects the maximum response error.? In our second example, we will use extreme value theory to model overflow rates in digital systems.? Even without knowing the underlying distributions of the data being analyzed, EVT can accurately estimate the rate at which a value will exceed a high threshold.

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