Earticle

초록

영어

The resolution of multy variable complex problems such as the multy speaker speech recognition and independently of context, requires the application of neural structures. One tool which proves to be powerful in the classification field, is the kohonen map called SOM. This map is characterized by the representation of static data. Thus, we ought to enrich the intelligibility and the performance of this model in order to reach what biology imposes by handling a kind of logical pile "memory" with the introduction of temporal context which realise feedbacks that integrate respectively the leaky integrators concept for the TKM. The recurrent leaky integrators idea for the recurrent SOM ‘RSOM’ in an improvement of the TKM. More recently, the principle of self refer for the recursive SOM. In other case, we are introducing the possibility to obtain hybridization with GA in an attempt to reach the natural evolution of the human thought as regards to recognition.

목차

Abstract
 1. Introduction
 2. Kohonen model: the map SOM
  2.1. General aspect
  2.2. Functional principle
 3. The temporal kohonen map: TKM
 4. The Recurrent SOM
 5. The Recursive SOM
 6. Other extensions
 7. The GASOM paradigm
 8. Conclusion

키워드

저자

• Mohamed Salah Salhi [ Laboratory of the Systems and Treatment of Signal (LSTS) National school Engineers of Tunis ]
• Najet Arous [ Laboratory of the Systems and Treatment of Signal (LSTS) National school Engineers of Tunis ]
• Noureddine Ellouze [ Laboratory of the Systems and Treatment of Signal (LSTS) National school Engineers of Tunis ]

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