Test data generation method of abstract state model based on recurrent neural network
A technology of cyclic neural network and test data, applied in the direction of biological neural network model, neural learning method, neural architecture, etc., can solve the problem that the internal state of cyclic neural network is difficult to test
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[0020] This patent implements the test data generation of the cyclic neural network through the fuzzy test of the abstract state model of the cyclic neural network. It mainly adopts the abstract model construction technology and the fuzzy testing technology. The specific key technologies involved include cyclic neural network (RNN), Abstract model construction technology, coverage-based fuzz testing technology, etc.
[0021] 1. Abstract model construction
[0022] In the present invention, we use the values of the internal neurons of the cyclic neural network to arrange in order to form the state vector of the cyclic neural network. We give the internal state and state relationship of the recurrent neural network model in a formal way, and use this as a basis to describe its characteristics. A neural network can be abstractly represented as a differentiable parameterized function f() whose input can be vectorized as x∈X,. After the cyclic neural network receives an input x...
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