Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this work a diagnostic approach for nonlinear systems is presented. The diagnosis is performed resorting to a neural predictor of the output of the system, and by using the error prediction as a feature for the diagnosis. A locally recurrent neural network is used as predictor, after it has been trained on a reference behavior of the system. In order to model the system under test a novel training algorithm that uses an explicit calculation of the cost function gradient is proposed. The residuals of the prediction are affected by the deviation of the parameters from their nominal values. In this way, by a simple statistical analysis of the residuals,  can perform a diagnosis of the system. The Rossler hyperchaotic system is used as benchmark problem in order to validate the diagnostic neural approach proposed.
['Sara Carcangiu', 'Augusto Montisci', 'Patrizia Boi']
I am writing a research paper on a idea A Training Algorithm for Locally Recurrent NN Based on Explicit Gradient of Error in Fault Detection Problems
[{"from": "human", "value": "I am writing a research paper on a idea A Training Algorithm for Locally Recurrent NN Based on Explicit Gradient of Error in Fault Detection Problems"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this work a diagnostic approach for nonlinear systems is presented. The diagnosis is performed resorting to a neural predictor of the output of the system, and by using the error prediction as a feature for the diagnosis. A locally recurrent neural network is used as predictor, after it has been trained on a reference behavior of the system. In order to model the system under test a novel training algorithm that uses an explicit calculation of the cost function gradient is proposed. The residuals of the prediction are affected by the deviation of the parameters from their nominal values. In this way, by a simple statistical analysis of the residuals,  can perform a diagnosis of the system. The Rossler hyperchaotic system is used as benchmark problem in order to validate the diagnostic neural approach proposed."}]