Title : 
Modeling stripline discontinuities by neural network with knowledge-based neurons
         
        
            Author : 
Wang, Bing-Zhong ; Zhao, Deshuang ; Hong, Jingsong
         
        
            Author_Institution : 
Inst. of Appl. Phys., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
         
        
        
        
        
            fDate : 
11/1/2000 12:00:00 AM
         
        
        
        
            Abstract : 
A three-layer neural network with knowledge-based neurons in the hidden layer (NNKBN) is presented for modeling stripline discontinuities. In NNKBN, prior knowledge for stripline discontinuity is incorporated into each hidden neuron. With knowledge-based neurons, the learning ability and generalization of the neural network are improved. Compared with conventional multi-layer perceptron neural network, the NNKBN can map the input-output relationships with fewer hidden neurons and has higher reliability for extrapolation beyond training data range. Two examples are given to illustrate the potential power of this approach.
         
        
            Keywords : 
circuit CAD; digital integrated circuits; extrapolation; high-speed integrated circuits; integrated circuit design; integrated circuit modelling; learning (artificial intelligence); multilayer perceptrons; strip line discontinuities; HSDICs; extrapolation; hidden layer; high-speed digital ICs; input-output relationships; knowledge-based neurons; learning ability; stripline discontinuities; three-layer neural network; training data range; Artificial neural networks; Extrapolation; Multi-layer neural network; Multilayer perceptrons; Neural networks; Neurons; Stripline; Training data; Transmission line discontinuities; Vectors;
         
        
        
            Journal_Title : 
Advanced Packaging, IEEE Transactions on
         
        
        
        
        
            DOI : 
10.1109/6040.883760