Title :
Existence of binary invariant sets in feedback neural networks with application to synthesis
Author_Institution :
Info-Com Dept., Rome Univ., Italy
fDate :
1/1/1993 12:00:00 AM
Abstract :
The design of fully connected discrete-time neural networks, with threshold units, can be performed by solving a set of linear inequalities. Using this formulation, the design problem can be handled by several powerful algorithms. This approach is extended to the design of continuous-time neural networks with sigmoidal units, which represent a more realistic model of analog circuit implementations. The proposed method is based on some theoretical results proved in this paper
Keywords :
neural nets; set theory; binary invariant sets; continuous-time neural networks; design; feedback neural networks; sigmoidal units; Algorithm design and analysis; Analog circuits; Cybernetics; Equations; Information processing; Integrated circuit interconnections; Intelligent networks; Network synthesis; Neural networks; Neurofeedback;
Journal_Title :
Neural Networks, IEEE Transactions on
