Publication detail

String Pattern Recognition Using Evolving Spiking Neural Networks and Quantum Inspired Particle Swarm Optimization

MICHLOVSKÝ, Z.

Original Title

String Pattern Recognition Using Evolving Spiking Neural Networks and Quantum Inspired Particle Swarm Optimization

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

This paper presents a novel method for string classification using ESNN-QiPSO. The experiments have shown that ESNN with parameter optimization and using a small number of features produces promising results that is significant for future exploration.  Other work includes how to find a more effective method for choosing the most relevant features and eliminating irrelevant features.

Keywords

String Kernels - Text Classification - Evolving Spiking Neural Network - Particle Swarm - Quantum Computing

Authors

MICHLOVSKÝ, Z.

RIV year

2009

Released

15. 12. 2009

Publisher

Springer Verlag

Location

Berlin / Heidelberg

ISBN

978-3-642-10682-8

Book

Neural Information Processing

Edition

Lecture Notes in Computer Science

Pages from

611

Pages to

619

Pages count

9

BibTex

@inproceedings{BUT34296,
  author="Zbyněk {Michlovský}",
  title="String Pattern Recognition Using Evolving Spiking Neural Networks and Quantum Inspired Particle Swarm Optimization",
  booktitle="Neural Information Processing",
  year="2009",
  series="Lecture Notes in Computer Science",
  pages="611--619",
  publisher="Springer Verlag",
  address="Berlin / Heidelberg",
  isbn="978-3-642-10682-8"
}