Generating simplified models for XiL systems
A technology for simplifying models and models, applied in general control systems, biological neural network models, control/regulation systems, etc., can solve problems such as unusable models
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[0037] The following is based on figure 1 The method for generating a simplified model for use in the XiL system according to the present invention is explained in more detail. In a first step 1 , at least one specified parameter that quantitatively characterizes the complexity of the model is determined for at least one starting model. In this case, the parameters may be specified during the course of the method or may have been specified and predefined. It is also possible to determine a plurality of prescribed parameters for the activation model that quantitatively characterize the complexity of the activation model.
[0038] In a next step 2, input data and output data of at least one starting model are generated. In step 3, using the generated training set of input data and output data of the at least one priming model to train the neural network to generate or develop a simplified model, wherein the simplified model has a lower complexity than the complexity of the at ...
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