Title :
Neural network clusters and cellular automata for the detection and classification of overlapping transient signals on radio astronomy spectrograms from spacecraft
Author :
deLassus, H. ; Lecacheux, A. ; Thiria, S. ; Badran, F.
Author_Institution :
Lab. ARPEGES, Obs. de Paris, Meudon, France
Abstract :
We address the problem of automatic detection and classification on spectrograms of mixed planetary low frequency radio signals with additive plasma noise. The signals and the noise under study are overlapping, nonGaussian, non stationary and non linear. The data obtained from spacecraft telemetry are irregularly sampled. We show a series of preprocessings that enables the use of neural networks. A cluster of time delay neural networks is then used to observe the signals from many windows. The different outputs of the time delay neural networks are the inputs of multi layer perceptrons which yield an intermediate classification. Cellular automata with a look up table of rules derived from the physical laws governing the radio electric phenomena do the find pattern recognition in a deterministic number of iterations
Keywords :
astronomy computing; cellular automata; delays; multilayer perceptrons; noise; pattern classification; radioastronomical techniques; signal detection; signal sampling; space telemetry; spectral analysis; table lookup; transient analysis; additive plasma noise; cellular automata; classification; detection; intermediate classification; iteration; look up table; multi layer perceptrons; neural network clusters; overlapping transient signals; pattern recognition; planetary low frequency radio signals; preprocessings; radio astronomy spectrograms; spacecraft telemetry; time delay neural networks; Additive noise; Cellular neural networks; Delay effects; Frequency; Low-frequency noise; Neural networks; Plasmas; RF signals; Space vehicles; Spectrogram;
Conference_Titel :
Time-Frequency and Time-Scale Analysis, 1996., Proceedings of the IEEE-SP International Symposium on
Conference_Location :
Paris
Print_ISBN :
0-7803-3512-0
DOI :
10.1109/TFSA.1996.547461