| Patent Number |
Title Of Patent |
Date Issued |
| 5802507 |
Method for constructing a neural device for classification of objects |
September 1, 1998 |
| On the basis of a device without hidden neurons, arbitrary samples are taken from a set of learning samples so as to be presented as objects to be classified. Each time if the response is not correct, a hidden neuron (H.sub.i) is introduced with a connection to the output neuron (O.sub.j |
| 5717687 |
Data communication system with adaptive routing, and switching node intended to be used in such |
February 10, 1998 |
| An adaptive routing protocol for a data communication system that operates in the connection mode. Therefore, the nodes have a function of detecting their neighboring nodes, which permits establishing sessions with their neighbors without previously knowing them, so as to transmit to the |
| 5649067 |
Neural device and method of constructing the device |
July 15, 1997 |
| On the basis of a device without hidden neurons, arbitrary samples are taken from a set of learning samples so as to be presented as objects to be classified. Each time if the response is not correct, a hidden neuron (H.sub.i) is introduced with a connection to the output neuron (O.sub.j |
| 5568591 |
Method and device using a neural network for classifying data |
October 22, 1996 |
| Method and device having a neural network for classifying data, and verification device for signatures.The device includes a neural network with an input layer 3, an internal layer 4, and an output layer 5. This network is designed to classify data vectors to classes, the synaptic weight |
| 5481604 |
Telecommunication network and searching arrangement for finding the path of least cost |
January 2, 1996 |
| The arrangement is formed by the presence in each node of the network of a cellular automaton comprising cells (0 to 8) interconnected by lines, so that the entirety of the cells and of the lines represents the nodes and the links respectively of the network while each cell comprises |
| 5455892 |
Method for training a neural network for classifying an unknown signal with respect to known sig |
October 3, 1995 |
| The device includes a neural network with an input layer 3, an internal layer 4, and an output layer 5. This network is designed to classify data vectors to classes, the synaptic weights in the network being determined through programming on the basis of specimens whose classes are known |
