Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Based on the classical backpropagation ight update equations, sliding mode control theory is introduced as a technique to adapt ights of a multi-layer perceptron. As will be demonstrated, the introduction of sliding mode has resulted in a much faster version of the standard backpropagation. The results show also that the proposed algorithm presents some important features of sliding mode control, which are robustness and high speed of learning. In addition to that, this paper shows also how control theory can be applied to train neural networks
['G.G. Parma', 'Benjamin Rodrigues de Menezes', 'Antônio de Pádua Braga']
I am writing a research paper on a idea Neural networks learning with sliding mode control: the sliding mode backpropagation algorithm.
[{"from": "human", "value": "I am writing a research paper on a idea Neural networks learning with sliding mode control: the sliding mode backpropagation algorithm."}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Based on the classical backpropagation ight update equations, sliding mode control theory is introduced as a technique to adapt ights of a multi-layer perceptron. As will be demonstrated, the introduction of sliding mode has resulted in a much faster version of the standard backpropagation. The results show also that the proposed algorithm presents some important features of sliding mode control, which are robustness and high speed of learning. In addition to that, this paper shows also how control theory can be applied to train neural networks"}]