SwePub
Sök i LIBRIS databas

  Extended search

onr:"swepub:oai:research.chalmers.se:ac55ad81-399f-4ebe-bc58-56575dd7bbd0"
 

Search: onr:"swepub:oai:research.chalmers.se:ac55ad81-399f-4ebe-bc58-56575dd7bbd0" > Diffusion Estimatio...

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Diffusion Estimation Over Cooperative Multi-Agent Networks With Missing Data

Gholami, Mohammad Reza, 1976 (author)
Jansson, Magnus (author)
KTH,Signalbehandling,ACCESS Linnaeus Centre
Ström, Erik, 1965 (author)
Chalmers tekniska högskola,Chalmers University of Technology
show more...
Sayed, Ali H. (author)
show less...
 (creator_code:org_t)
IEEE, 2016
2016
English.
In: IIEEE Transactions on Signal and Information Processing over Networks. - : IEEE. - 2373-776X. ; 2:3, s. 276-289
  • Journal article (peer-reviewed)
Abstract Subject headings
Close  
  • In many fields, and especially in the medical and social sciences and in recommender systems, data are gathered through clinical studies or targeted surveys. Participants are generally reluctant to respond to all questions in a survey or they may lack information to respond adequately to some questions. The data collected from these studies tend to lead to linear regression models where the regression vectors are only known partially: some of their entries are either missing completely or replaced randomly by noisy values. In this work, assuming missing positions are replaced by noisy values, we examine how a connected network of agents, with each one of them subjected to a stream of data with incomplete regression information, can cooperate with each other through local interactions to estimate the underlying model parameters in the presence of missing data. We explain how to adjust the distributed diffusion strategy through (de)regularization in order to eliminate the bias introduced by the incomplete model. We also propose a technique to recursively estimate the (de)regularization parameter and examine the performance of the resulting strategy. We illustrate the results by considering two applications: one dealing with a mental health survey and the other dealing with a household consumption survey.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
NATURVETENSKAP  -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
NATURAL SCIENCES  -- Mathematics -- Probability Theory and Statistics (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)

Keyword

distributed estimation
regularization
diffusion strategy
mean-squareerror
Missing data
linear regression

Publication and Content Type

art (subject category)
ref (subject category)

Find in a library

To the university's database

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Search outside SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view