Variable binding in a neural network using a distributed representation

Neuron Mathematical Model Representation of Neural Tensor Network for RDF Knowledge Base Completion

In this paper, a state-of-the-art neuron mathematical model of neural tensor network (NTN) is proposed to RDF knowledge base completion problem. One of the difficulties with the parameter of the network is that representation of its neuron mathematical model is not possible. For this reason, a new representation of this network is suggested that solves this difficulty. In the representation, th...

Proposing A Distributed Model For Intrusion Detection In Mobile Ad-Hoc Network Using Neural Fuzzy Interface

Security term in mobile ad hoc networks has several aspects because of the special specification of these networks. In this paper a distributed architecture was proposed in which each node performed intrusion detection based on its own and its neighbors’ data. Fuzzy-neural interface was used that is the composition of learning ability of neural network and fuzzy Ratiocination of fuzzy system as...

Proposing A Distributed Model For Intrusion Detection In Mobile Ad-Hoc Network Using Neural Fuzzy Interface

Security term in mobile ad hoc networks has several aspects because of the special specification of these networks. In this paper a distributed architecture was proposed in which each node performed intrusion detection based on its own and its neighbors’ data. Fuzzy-neural interface was used that is the composition of learning ability of neural network and fuzzy Ratiocination of fuzzy system as...

Symbols Among the Neurons: Details of a Connectionist Inference Architecture

Pattern matching and variable binding are easily implemented in conventional computer architectures, but not necessarily in all architectures. In a distributed neural network architecture each symbol is represented by activity in many units and each unit contributes to the representation of many symbols. Manipulating symbols using this type of distributed representation is not as easy as with a...

Representation of Adsorption Data for the Case of Energetically Heterogeneous Solid Surfaces Using Artificial Neural Network