A modification of Veto logic for a committee of threshold logic units and the use of 2-class classifiers for function estimation Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/g158bm777

Descriptions

Attribute NameValues
Creator
Abstract or Summary
  • The well-known local adjustment algorithm for training a threshold logic unit, TLU, is extended to a local adjustment algorithm for training a network of TLUs Computer simulations show that the extension is unsatisfactory. A new logic for a committee of TLUs, called modified veto logic, and a local adjustment algorithm for training a modified veto committee are described. Unlike a majority committee, a modified veto committee may have members added during training, and the modified veto committee is free to attain a size needed to solve a problem. Computer simulations show that a modified veto committee can solve difficult pattern recognition problems and, in the instances tested, does so more successfully than a majority committee. A technique for using a number of 2-class classifiers to perform function estimation is described. The 2-class classifiers are trained on a set of ordered pairs belonging to the function being estimated; no information about the form of the function is needed; the function can have any number of independent variables; and the accuracy of the estimate increases with the number of 2-class classifiers used. Computer simulations on artificially generated data and on "real life" data show that this technique provides accurate estimates of functions. It is shown that replacing non-binary variables by binary variables can greatly increase the recognition rate of a TLU.
Resource Type
Date Available
Date Copyright
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Academic Affiliation
Non-Academic Affiliation
Subject
Rights Statement
Peer Reviewed
Language
Digitization Specifications
  • File scanned at 300 ppi (Monochrome) using Capture Perfect 3.0.82 on a Canon DR-9080C in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
Replaces
Additional Information
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2014-02-25T17:08:47Z (GMT) No. of bitstreams: 1 OsborneMartin1975.pdf: 2135335 bytes, checksum: e1e80136e4fd02fd55aaabd7f2ffaf8b (MD5)
  • description.provenance : Submitted by Georgeann Booth (gbscannerosu@gmail.com) on 2014-01-15T22:41:30Z No. of bitstreams: 1 OsborneMartin1975.pdf: 2135335 bytes, checksum: e1e80136e4fd02fd55aaabd7f2ffaf8b (MD5)
  • description.provenance : Made available in DSpace on 2014-02-25T17:08:47Z (GMT). No. of bitstreams: 1 OsborneMartin1975.pdf: 2135335 bytes, checksum: e1e80136e4fd02fd55aaabd7f2ffaf8b (MD5) Previous issue date: 1974-11-19
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2014-01-16T15:27:05Z (GMT) No. of bitstreams: 1 OsborneMartin1975.pdf: 2135335 bytes, checksum: e1e80136e4fd02fd55aaabd7f2ffaf8b (MD5)

Relationships

In Administrative Set:
Last modified: 08/17/2017

Downloadable Content

Download PDF
Citations:

EndNote | Zotero | Mendeley

Items