STORING PATTERNS IN HAMILTONIAN NEURAL NETWORKS
ALEXEI B. POTAPOV, Mazhar Ali · International Journal of Modern Physics C · 2001
We consider a number of techniques for storing patterns in orthogonal normal modes of a Hamiltonian system. Such techniques, along with the method of selecting the most excited mode, enable us to introduce a new class of pattern recognition systems that we call Hamiltonian neural networks. In contrast to all traditional neural networks, our Hamiltonian neural networks are nondissipative. Quantization of the Hamiltonian of our network is expected to serve as a means for future work on quantum analogs of classical information processing.