Einsteinian neural network for spectrum estimation

Neural Networks

Volumn 10, Issue 9, 1997, Pages 1541-1546

  Perlovsky, Leonid I ^a   Plum, Charles P ^b   Franchi, Peter R ^b   Tichovolsky, Elihu J ^b   Choi, David ^b   Weijers, Bertus ^b  

^a Nichols Research   (United States)

^b NONE

Author keywords

Clutter; Entropy; Ionosphere; Model based; Neural networks; Propagation; Radar; Spectrum estimation

Indexed keywords

DATA REDUCTION; IONOSPHERIC ELECTROMAGNETIC WAVE PROPAGATION; LEARNING SYSTEMS; MATHEMATICAL MODELS; PROBABILITY; RADAR CLUTTER; SPECTRUM ANALYSIS; TELECOMMUNICATION LINKS;

ENTROPY MAXIMIZATION PRINCIPLE; EQUATORIAL IONOSPHERIC CLUTTER; SPECTRUM ESTIMATION;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER ANALYSIS; COMPUTER PROGRAM; ELECTROMAGNETIC RADIATION; ENTROPY; FREQUENCY ANALYSIS; PRIORITY JOURNAL; SPECTRUM; TELECOMMUNICATION;

EID: 0031470249     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0893-6080(97)00081-6     Document Type: Article

References (14)

1. Dempster, A.P., Laird, N.M., & Rubin, D.B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, 39, 0.
2. Einstein, A., & Hopf, L. (1910). Über einen satz der wahrscheinlichkeitsrechnung und seine anwendung an die strahlungstheorie. Annals of Physics, 33, 1096-1104.
3. Franchi, P.R., & Tichovolsky, E.J. (1989). Phase Screen Modulation as a Source of Clutter Related Noise in Over-the-Horizon Radars, RADC-TR-89-296.
4. Perlovsky, L.I. (1987). Sensor Fusion and Neural Networks. DARPA Neural Network Study. Lexington, MA: MIT/Lincoln Laboratory.
5. Perlovsky, L.I. (1994). Model based neural net signal processing. Neural Networks, 7, 565-572.
6. Perlovsky, L.I. (1995). Tracking with MEANS. DARPA OTH Radar Workshop Proc., A147-173.
7. Perlovsky, L.I., & Jaskolski, J. (1994). ML adaptive neural controller. Neural Networks, 7, 671-679.
8. Perlovsky, L.I., & McManus, M.M. (1991). Maximum likelihood neural networks for sensor fusion and adaptive classification. Neural Networks, 4, 89-102.
9. Sakurai, J.J. (1985). Modern quantum mechanics. New York: Addison Wesley.
10. Specht, D.F. (1990). Probabilistic neural networks. Neural Networks, 3(1), 109-118.
11. Streit, R.L., & Luginbuhl, T.E. (1990). ML Neural Nets. TM no. 911277. New London, CT: NUWC.
12. Thomas, D. (1995). Clutter characterization. Adelaide: US/AS MoA Radar Research Meeting.
13. Vandrak, R.R., Smith, G., IIatfield, V.E., Tsunoda, R.T., Frank, V.R., & Perreault, P.D. (1977). Chatanika Model for the HF Propagation Prediction, RADC-TR-78-7. Menlo Park, CA: SRI.
14. Widrow, B. (1959). Adaptive sample data systems - a statistical theory of adaptation. 1959 WESCON convention record. Part, 4, 74-85.