Discrete Time Neural Network Synthesis Using Input and Output Activation Functions (CROSBI ID 78804)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Novaković, Branko
engleski
Discrete Time Neural Network Synthesis Using Input and Output Activation Functions
Abstract - A new very fast algorithm for synthesis of a new structure of discrete-time neural networks (NN) is proposed. For this purpose the following concepts are employed: (i) combination of input and output activation functions, (ii) input time-varying signal distribution, (iii) time-discrete domain synthesis and (iiii) one-step learning iteration approach. The problem of multiple input-output mappings of ( time-varying ) vectors is solved. Simulation results based on the synthesis of a new structure of feedforward NN of an universal logical unit are presented. The proposed NN synthesis procedure is useful for applications to identification and control of nonlinear, very fast, dynamical systems. In this sense a feedforward NN for an adaptive nonlinear robot control is designed. Finally, a new algorithm for the direct inverse modelling of input/output nonquadratic systems is discussed.
Neural networks; one-step learning; input and output activation functions; discrete time
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o izdanju
26 (4)
1996.
533-541-x
objavljeno
1083-4419
10.1109/3477.517029
Povezanost rada
Strojarstvo