Abstract
The author compares the class of languages that can be recognized by a logical neural network (LNN) with the classes of languages in Chomsky hierarchy. The computability of LNN is studied. The computation power of LNN is identical to the computation of a probabilistic automaton, that is, it is possible to recognize more than finite state languages with such machines. This indicates what can be expected from LNN, i.e. which functions this kind of network can learn. >
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.