Real-Time Neural Networks for Information Propagation of Load Vehicles in Remote

원격지 자동차의 정보 전송을 위한 실시간 신경망

For real-time recognizing of the load vehicles a new Neural Network algorithm 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 severa simulation experiments, real time reconstruction nonlinear image information is Processed. 1-D hardware has been composed and various experi with static and dynamic signals have implemented.