Patent
1993-06-22
1995-03-28
MacDonald, Allen R.
G06F 1518
Patent
active
054025222
ABSTRACT:
A dynamically stable associative learning neural network system include a plurality of synapses (122,22-28), a non-linear function circuit (30) and an adaptive weight circuit (150) for adjusting the weight of each synapse based upon the present signal and the prior history of signals applied to the input of the particular synapse and the present signal and the prior history of signals applied to the input of a predetermined set of other synapses. An embodiment of a conditional-signal neuron circuit (100) receives input signals from conditional stimuli and an unconditional-signal neuron circuit (110) receives input signals from unconditional stimuli. A neural network (200) is formed by a set of conditional-signal and unconditional-signal neuron circuits connected by flow-through synapses to form separate paths between each input (215) and a corresponding output (245). In one embodiment, the neural network (200) is initialized by varying the weight of the input signals from conditional stimuli, until a dynamic equilibrium is reached.
Alkon Daniel L.
Blackwell Kim L.
Vogl Thomas P.
Environmental research Institute of Michigan
MacDonald Allen R.
The United States of America as represented by the Department of
LandOfFree
Dynamically stable associative learning neural system does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Dynamically stable associative learning neural system, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Dynamically stable associative learning neural system will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-2257783