Information Propagation Neural Networks for Real-time Recognition of Load Vehicles

도로 장애물의 실시간 인식을 위한 정보전파 신경회로망

  • Kim, Jong-Man (Dept. of Electrical Electronical and Control Engineering Chonbuk University) ;
  • Kim, Hyong-Suk (Dept. of Electrical Electronical and Control Engineering Chonbuk University) ;
  • Kim, Sung-Joong (Dept. of Electrical Electronical and Control Engineering Chonbuk University) ;
  • Sin, Dong-Yong (Dept. of Radial Rays Hanra College)
  • 김종만 (전북대학교 전기전자제어공학부) ;
  • 김형석 (전북대학교 전기전자제어공학부) ;
  • 김성중 (전북대학교 전기전자제어공학부) ;
  • 신동용 (한라대학 방사선과)
  • Published : 1999.07.19

Abstract

For the safty driving of an automobile which is become individual requisites, a new Neural Network algorithm which recognized the load vehicles in real time is proposed. The proposed neural network technique is the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. The most reliable algorithm derived for real time recognition of vehicles, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates. Through several simulation experiments, real time reconstruction of the nonlinear image information is processed 1-D LIPN hardware has been composed and various experiments with static and dynamic signals have been implmented.

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