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DTSTART;TZID=America/Los_Angeles:20250820T113000
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DESCRIPTION:Abstract: Complex systems seen either in general engineering pr
 actice or economics are subjected to ever increased uncertainties that are
  mostly represented as random variables or parameters\, and the characteri
 stics of random variables are represented by their probability density fun
 ctions (PDFs). Controlling their PDFs means to shape their stochastic dist
 ributions and in general it would provide a full treatment for system anal
 ysis and operational control and optimization. This leads to the developme
 nt of stochastic distribution control (SDC) systems theory in the past dec
 ades\, where the original aim of the controller design is to realize a sha
 pe control of the distributions of certain random variables in their PDFs 
 sense for some engineering processes. Indeed\, once the PDFs of these rand
 om variables or parameters are used to describe their distribution charact
 ers\, the control task is to obtain control signals so that the output PDF
 s of stochastic systems are made to follow their target PDFs.\n\nThe subje
 ct of SDC was initially originated for non-Gaussian stochastic control sys
 tems design but has found a wide spectrum of applications in general syste
 ms in terms of data-driven modeling\, analysis\, signal processing (filter
 ing)\, data mining via multivariable statistics\, decision-making (optimiz
 ation) for systems subjected to uncertainties and even in economics. In th
 is context\, SDC constitutes an effective primer tool for complex system a
 nalysis\, control and operational optimizations.\n\nIn this talk\, a detai
 led survey of the developments on the research of SDC systems will be made
  together with their wide spectrum applications and future perspectives.\n
 \nSpeaker(s): \, Prof. Wang\n\nAgenda: \n11:30AM-12:30PM Presentation\n\n1
 2:30PM-1:00PM Q&A\n\nVirtual: https://events.vtools.ieee.org/m/495985
LOCATION:Virtual: https://events.vtools.ieee.org/m/495985
ORGANIZER:maliangp@yahoo.com
SEQUENCE:35
SUMMARY:Stochastic Distribution Control and Its Applications
URL;VALUE=URI:https://events.vtools.ieee.org/m/495985
X-ALT-DESC:Description: <br /><p class="xmsonormal"><strong><span style="fo
 nt-size: 11.0pt\;">Abstract: </span></strong><span style="font-size: 11.0p
 t\;">Complex systems seen either in general engineering practice or econom
 ics are subjected to ever increased uncertainties that are mostly represen
 ted as random variables or parameters\, and the characteristics of random 
 variables are represented by their probability density functions (PDFs). C
 ontrolling their PDFs means to shape their stochastic distributions and in
  general it would provide a full treatment for system analysis and operati
 onal control and optimization. This leads to the development of stochastic
  distribution control (SDC) systems theory in the past decades\, where the
  original aim of the controller design is to realize a shape control of th
 e distributions of certain random variables in their PDFs sense for some e
 ngineering processes. Indeed\, once the PDFs of these random variables or 
 parameters are used to describe their distribution characters\, the contro
 l task is to obtain control signals so that the output PDFs of stochastic 
 systems are made to follow their target PDFs.&nbsp\;</span></p>\n<p class=
 "xmsonormal"><span style="font-size: 11.0pt\;">The subject of SDC was init
 ially originated for non-Gaussian stochastic control systems design but ha
 s found a wide spectrum of applications in general systems in terms of dat
 a-driven modeling\, analysis\, signal processing (filtering)\, data mining
  via multivariable statistics\, decision-making (optimization) for systems
  subjected to uncertainties and even in economics. In this context\, SDC c
 onstitutes an effective primer tool for complex system analysis\, control 
 and operational optimizations.</span></p>\n<p class="xmsonormal"><span sty
 le="font-size: 11.0pt\;">In this talk\, a detailed survey of the developme
 nts on the research of SDC systems will be made together with their wide s
 pectrum applications and future perspectives.</span></p><br /><br />Agenda
 : <br /><p>11:30AM-12:30PM Presentation</p>\n<p>12:30PM-1:00PM Q&amp\;A</p
 >
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