Modern Analytic Techniques to Solve the Dynamics of Recurrent Neural Networks
Advances in Neural Information Processing Systems 8 (1995) 253-259
Abstract:
We describe the use of modern analytical techniques in solving the dynamics of symmetric and nonsymmetric recurrent neural networks near saturation. These explicitly take into account the correlations between the post-synaptic potentials, and thereby allow for a reliable prediction of transients.A memory model with novel behaviour in sequential learning
Network Computation in Neural Systems Taylor & Francis 6:3 (1995) 415-427
A MEMORY MODEL WITH NOVEL BEHAVIOR IN SEQUENTIAL LEARNING
NETWORK-COMPUTATION IN NEURAL SYSTEMS 6:3 (1995) 415-427
ATOMIC TUNNELING FROM A SCANNING-TUNNELING OR ATOMIC-FORCE MICROSCOPE TIP - DISSIPATIVE QUANTUM EFFECTS FROM PHONONS
PHYSICAL REVIEW LETTERS 74:8 (1995) 1363-1366
COMPETITION BETWEEN PATTERN RECALL AND SEQUENCE PROCESSING IN A NEURAL-NETWORK STORING CORRELATED PATTERNS
JOURNAL OF PHYSICS A-MATHEMATICAL AND GENERAL 28:12 (1995) 3421-3437