BEGIN:VCALENDAR
VERSION:2.0
CALSCALE:GREGORIAN
PRODID:UW-Madison-Physics-Events
BEGIN:VEVENT
SEQUENCE:0
UID:UW-Physics-Event-1462
DTSTART:20090428T170500Z
DURATION:PT1H0M0S
DTSTAMP:20260422T232533Z
LAST-MODIFIED:20090216T144419Z
LOCATION: 4274 Chamberlin
SUMMARY:Applications of neural networks in time-series analysis\, Chao
 s & Complex Systems Seminar\, Adam Maus\, UW Department of Physics
DESCRIPTION:Artificial neural networks are mathematical models that em
 ulate biological neural systems.  They have been used in classificatio
 n\, pattern recognition\, and time-series analysis.  In time-series an
 alysis\, neural networks can be used for forecasting but also to deter
 mine how many and which past values are required to predict the future
 .  Determination of this 'lag space' sheds light on the nature of the 
 dynamics and permits development of minimal models capable of replicat
 ing the dynamics. I will highlight applications of neural networks in 
 the real world as models that classify\, forecast\, and analyze data w
 hile emphasizing their use in determining the lag space. 
URL:https://www.physics.wisc.edu/events/?id=1462
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