Abstract
We introduce a novel genetic programming (GP) technique to evolve both the structure and parameters of adaptive digital signal processing algorithms. This is accomplished by defining a set of node functions and terminals to implement the basic operations commonly used in a large class of DSP algorithms. In addition, we show how simulated annealing may be employed to assist the GP in optimizing the numerical parameters of expression trees. The concepts are illustrated by using GP to evolve high performance algorithms for detecting binary data sequences at the output of a noisy, non-linear communications channel.
Original language | English |
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Pages (from-to) | 473-480 |
Number of pages | 8 |
Journal | IEE Conference Publication |
Issue number | 414 |
Publication status | Published - 1 Jan 1995 |
Event | Proceedings of the 1st IEE/IEEE International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications GALESIA '95 - Sheffield, Engl Duration: 12 Sept 1995 → 14 Sept 1995 |
Keywords
- genetic algorithms
- digital signal processing
- learning algorithms
- communication channels (information theory)
- mathematical operators
- binary sequences