Titlebook: Neural Networks; EURASIP Workshop 199 Luis B. Almeida,Christian J. Wellekens Conference proceedings 1990 Springer-Verlag Berlin Heidelberg

ADAGE

Synthesize

Colonnade

等級的上升

DAMN

Meditate

Stability of the random neural network model,odelling inhibitory and excitatory signals. They are summed at the input of each neuron and constitute its signal potential. The state of each neuron in this model is its signal potential, while the network state is the vector of signal potentials at each neuron. If its potential is positive, a neur

IRS

Temporal pattern recognition using EBPS,eference to some simple examples of Temporal Pattern Recognition..It is shown that this network can learn features which are invariant under translation in time and that no temporal alignment of the inputs is required. The main concern of this paper is that the constraining of weights in full recurr

袖章

,The “moving targets” training algorithm, with arbitrary feedback. The algorithm resembles back-propagation in that an error function is minimized using a gradient-based method, but the optimization is carried out in the hidden part of state space either instead of, or in addition to weight space. A straightforward adaptation of this metho

HUMID

存心