Satellite Frequency Assignments Using Transiently Chaotic Neural Networks with Variable Thresholds
نویسندگان
چکیده
The objective of the satellite frequency assignment problem (FAP) is to minimize the cochannel interference between two satellite systems by rearranging the frequency assignments. This NP-complete problem is difficult to solve, especially for large-size problems, and is yet growing in importance, since we increasingly depend on satellites to fulfill our communications needs. In this paper, we propose a transiently chaotic neural network with variable thresholds (TCNN-VT) by letting the threshold of a neuron vary with the interference of the assignment which the neuron represents. We apply this new model on the FAP in satellite communications.
منابع مشابه
Minimizing interference in satellite communications using transiently chaotic neural networks
The frequency assignment problem (FAP) in satellite communications is solved with transiently chaotic neural networks (TCNN). The objective of this optimization problem is to minimize cochannel interference between two satellite systems by rearranging the frequency assignments. For an N-carrier–M-segment FAP problem, we construct a TCNN consisting of N ×M neurons. The performance of the TCNN is...
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