Novel magnetic field computation model in pattern classification

Feng Pan*, Xiaoting Li, Ting Long, Xiaohui Hu, Tingting Ren, Junping Du

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Field computation, an emerging computation technique, has inspired passion of intelligence science research. A novel field computation model based on the magnetic field theory is constructed. The proposed magnetic field computation (MFC) model consists of a field simulator, a non-derivative optimization algorithm and an auxiliary data processing unit. The mathematical model is deduced and proved that the MFC model is equivalent to a quadratic discriminant function. Furthermore, the finite element prototype is derived, and the simulator is developed, combining with particle swarm optimizer for the field configuration. Two benchmark classification experiments are studied in the numerical experiment, and one notable advantage is demonstrated that less training samples are required and a better generalization can be achieved.

Original languageEnglish
Pages (from-to)862-869
Number of pages8
JournalJournal of Systems Engineering and Electronics
Volume24
Issue number5
DOIs
Publication statusPublished - 2013

Keywords

  • Field computation
  • Finite element analysis
  • Machine learning and pattern classification
  • Magnetic field computation (MFC)
  • Particle swarm optimization (PSO)

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