3/15/2024 0 Comments Finite state automata adalah![]() ![]() ![]() We compare our algorithm to other methods proposed in the literature.Ībstract = "Recurrent neural networks that are trained to behave like deterministic finite-state automata (DFAs) can show deteriorating performance when tested on long strings. For a DFA with n states and m input alphabet symbols, the constructive algorithm generates a "programmed" neural network with O(n) neurons and O(mn) weights. We derive a relationship between the weight strength and the number of DFA states for robust string classification. The algorithm is based on encoding strengths of weights directly into the neural network. We prove that a simple algorithm can construct second-order recurrent neural networks with a sparse interconnection topology and sigmoidal discriminant function such that the internal DFA state representations are stable, that is, the constructed network correctly classifies strings of arbitrary length. The use of a sigmoidal discriminant function together with the recurrent structure contribute to this instability. This deteriorating performance can be attributed to the instability of the internal representation of the learned DFA states. Recurrent neural networks that are trained to behave like deterministic finite-state automata (DFAs) can show deteriorating performance when tested on long strings. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |