Earticle

초록

영어

In this work, we develop a new method of setting the input to reservoir and reservoir to reservoir weights in echo state machines. We use a clustering technique which we have previously developed as a pre-processing stage to set the reservoir parameters which at this stage are prototypes. We then use these prototypes as weights in the standard architecture while setting the reservoir to output weights in a standard manner. We show results on a variety of data sets in the literature which show that this method out-performs a standard random echo state machine.

목차

Abstract
 1. Introduction
  1.1. Echo State Networks
  1.2. Data Clustering
 2. The Proposed Method
  2.1. Inverse Weighted K-means Algorithm IWK
  2.2. Supervised Learning
  2.3. The Algorithm
 3. Simulations
 4. Conclusion and Future Work
 References

키워드

저자

• Wesam M. Ashour [ Islamic University of Gaza, Palestine ]
• Abdallatif S. Abu-Issa [ Birzeit University, Palestine ]
• Olaf Hellwich [ Technical University of Berlin, Germany ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605