  In the present paper a newer application of Artificial Neural Network (ANN)
has been developed i.e., predicting response-function results of
electrical-mechanical system through ANN. This method is specially useful to
complex systems for which it is not possible to find the response-function
because of complexity of the system. The proposed approach suggests that how
even without knowing the response-function, the response-function results can
be predicted with the use of ANN to the system. The steps used are: (i)
Depending on the system, the ANN-architecture and the input & output parameters
are decided, (ii) Training & test data are generated from simplified circuits
and through tactic-superposition of it for complex circuits, (iii) Training the
ANN with training data through many cycles and (iv) Test-data are used for
predicting the response-function results. It is found that the proposed novel
method for response prediction works satisfactorily. Thus this method could be
used specially for complex systems where other methods are unable to tackle it.
In this paper the application of ANN is particularly demonstrated to
electrical-circuit system but can be applied to other systems too.
