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Year 2006, Volume: 6 Issue: 1, 97 - 105, 02.01.2012

Engin Avcı İbrahim Turkoglu Mustafa Poyraz

Abstract

References

  • Volt Ltd., vol. 1, p.p. 4-7 ,Canada, 1989.
  • Turkoglu, I., Hanbay D., “Artificial Neural Network and An Intelligent DTMF Signal Time-Frequency Analysis Using the Analytic Code Decoder on Based FFT” , 10. Signal Signal: Why the Complementary Distribution Processing and Comunication Applications (SİU2002) , p.p. 394-399 , Pamukkale/Denizli, Turkey, 2002.
  • Choi, I., S., Kim, H., T., “Efficient feature Extraction from time-frequency analysis of transient response for target identification”, Microwave and Optical Technology Letters Vol. 26, No: 6, p.p. 403-407, 2000.
  • Madrid J.J. M., Corredera J. R. C., Vela G. M., “A neural network approach to Doppler based target classification”, Radar 92. International Conference, pp. 450–453, Brighton, England, 1992.
  • Swiatnicki Z., Semklo R., “The artificialintelligence tools utilization in radar Technical Reports, AD-A299735, 1995. signal processing”, 12th International
  • Conference on Microwaves and Radar (MIKON Guangyi C., Applications of wavelet '98), vol. 3, pp. 799 –803, Krakow, Poland, Jakubiak A., Arabas J., Grabczak K., etc., “Radar clutter classification using Kohonen selection in radar target classification”, IEEE neural network”, Radar 97 (Conf. Publ. No. Transactions on Information Theory, vol. 46, pp. ), pp. 185 –188, Edinburgh , UK, 1997.
  • Turkoglu, I., Arslan, A. I., Erdoğan, “An expert system for diagnose of the heart valve diseases” , Expert systems with applications , (2002), 23(3) , 229-236, 2002.
  • Schreier, P., J., Scharf , L., L., “Stochastic Matterts”, IEEE Transactions on Sign Processing, (2003), Vol.51, No.12.p.p. 3071- , 2003.
  • Stankovic, L., “On the Realization of the Polynomial Wigner-Ville Distribution for Multicomponent Signals”, IEEE Signal Processing Letters, Vol. 5, No. 7, 1998.
  • Beastall W. D.,” Recognition of radar signals by neural network”, First IEE International Conference on Artificial Neural Networks, (Conf. Publ. No. 313), pp.139-142, London, UK, 1989.
  • Application of pattern recognition techniques for early warning radar, Nasa transforms in pattern recognition and de-noising, Concordia University (Canada), 1999.
  • Sowelam S.M., Tewfik A.H., “Waveform –1029, 2000.
  • Turkoğlu I., Arslan A., “Optimization of the Performance of Neural Network Based Pattern Recognition Classifiers with Distributed Systems”, IEEE Computer Society, International Conference on Parallel and Distributed Systems (ICPADS’2001), pp. 379-382, Kyong Ju, Korea, Jun. 26-29, 2001.
  • Passino, K., M., and Yurkovich, S., Fuzzy Control, Adisson Wesley Longman, Inc., California, pp.259-267, 1998.
  • Avci, E., Turkoglu, I., “Modeling of Tunnel Diode by Adaptive-Network-Based Fuzzy Inference System” , International Journal of Computational Intelligence , ISSN 1304- , (2003), Volume:1, Number:1 , p.p. 231
  • Kosko, B., Neural Networks and Fuzzy Systems, A Dynamical Systems Approach, Englewood Ciffs., NJ: Prentice Hall, 1991.
  • Jang, J. S. R., Sun, C. T., Neuro-Fuzzy Modeling and Control, proceedings of the IEEE, vol. 83, No. 3, 1995.
  • Jang, J. S. R., ANFIS: Adaptive network- based fuzzy inference systems,IEEE, Trans. Syst., Man. and Cybern., vol. 23, pp. 665-685,

THE PERFORMANCE ANALYSIS OF STFT-ANFIS CLASSIFICATION METHOD ON PULSED RADAR TARGET CATEGORIZATION

Year 2006, Volume: 6 Issue: 1, 97 - 105, 02.01.2012

Engin Avcı İbrahim Turkoglu Mustafa Poyraz

Abstract

THE PERFORMANCE ANALYSIS OF STFT-ANFIS CLASSIFICATION METHOD ON PULSED RADAR TARGET CATEGORIZATION

Keywords

Feature extraction ANFIS radar target classification STFT

References

  • Volt Ltd., vol. 1, p.p. 4-7 ,Canada, 1989.
  • Turkoglu, I., Hanbay D., “Artificial Neural Network and An Intelligent DTMF Signal Time-Frequency Analysis Using the Analytic Code Decoder on Based FFT” , 10. Signal Signal: Why the Complementary Distribution Processing and Comunication Applications (SİU2002) , p.p. 394-399 , Pamukkale/Denizli, Turkey, 2002.
  • Choi, I., S., Kim, H., T., “Efficient feature Extraction from time-frequency analysis of transient response for target identification”, Microwave and Optical Technology Letters Vol. 26, No: 6, p.p. 403-407, 2000.
  • Madrid J.J. M., Corredera J. R. C., Vela G. M., “A neural network approach to Doppler based target classification”, Radar 92. International Conference, pp. 450–453, Brighton, England, 1992.
  • Swiatnicki Z., Semklo R., “The artificialintelligence tools utilization in radar Technical Reports, AD-A299735, 1995. signal processing”, 12th International
  • Conference on Microwaves and Radar (MIKON Guangyi C., Applications of wavelet '98), vol. 3, pp. 799 –803, Krakow, Poland, Jakubiak A., Arabas J., Grabczak K., etc., “Radar clutter classification using Kohonen selection in radar target classification”, IEEE neural network”, Radar 97 (Conf. Publ. No. Transactions on Information Theory, vol. 46, pp. ), pp. 185 –188, Edinburgh , UK, 1997.
  • Turkoglu, I., Arslan, A. I., Erdoğan, “An expert system for diagnose of the heart valve diseases” , Expert systems with applications , (2002), 23(3) , 229-236, 2002.
  • Schreier, P., J., Scharf , L., L., “Stochastic Matterts”, IEEE Transactions on Sign Processing, (2003), Vol.51, No.12.p.p. 3071- , 2003.
  • Stankovic, L., “On the Realization of the Polynomial Wigner-Ville Distribution for Multicomponent Signals”, IEEE Signal Processing Letters, Vol. 5, No. 7, 1998.
  • Beastall W. D.,” Recognition of radar signals by neural network”, First IEE International Conference on Artificial Neural Networks, (Conf. Publ. No. 313), pp.139-142, London, UK, 1989.
  • Application of pattern recognition techniques for early warning radar, Nasa transforms in pattern recognition and de-noising, Concordia University (Canada), 1999.
  • Sowelam S.M., Tewfik A.H., “Waveform –1029, 2000.
  • Turkoğlu I., Arslan A., “Optimization of the Performance of Neural Network Based Pattern Recognition Classifiers with Distributed Systems”, IEEE Computer Society, International Conference on Parallel and Distributed Systems (ICPADS’2001), pp. 379-382, Kyong Ju, Korea, Jun. 26-29, 2001.
  • Passino, K., M., and Yurkovich, S., Fuzzy Control, Adisson Wesley Longman, Inc., California, pp.259-267, 1998.
  • Avci, E., Turkoglu, I., “Modeling of Tunnel Diode by Adaptive-Network-Based Fuzzy Inference System” , International Journal of Computational Intelligence , ISSN 1304- , (2003), Volume:1, Number:1 , p.p. 231
  • Kosko, B., Neural Networks and Fuzzy Systems, A Dynamical Systems Approach, Englewood Ciffs., NJ: Prentice Hall, 1991.
  • Jang, J. S. R., Sun, C. T., Neuro-Fuzzy Modeling and Control, proceedings of the IEEE, vol. 83, No. 3, 1995.
  • Jang, J. S. R., ANFIS: Adaptive network- based fuzzy inference systems,IEEE, Trans. Syst., Man. and Cybern., vol. 23, pp. 665-685,
There are 18 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Engin Avcı This is me

İbrahim Turkoglu

Mustafa Poyraz This is me

Publication Date January 2, 2012
Published in Issue Year 2006 Volume: 6 Issue: 1

Cite

APA Avcı, E., Turkoglu, İ., & Poyraz, M. (2012). THE PERFORMANCE ANALYSIS OF STFT-ANFIS CLASSIFICATION METHOD ON PULSED RADAR TARGET CATEGORIZATION. IU-Journal of Electrical & Electronics Engineering, 6(1), 97-105.
AMA Avcı E, Turkoglu İ, Poyraz M. THE PERFORMANCE ANALYSIS OF STFT-ANFIS CLASSIFICATION METHOD ON PULSED RADAR TARGET CATEGORIZATION. IU-Journal of Electrical & Electronics Engineering. January 2012;6(1):97-105.
Chicago Avcı, Engin, İbrahim Turkoglu, and Mustafa Poyraz. “THE PERFORMANCE ANALYSIS OF STFT-ANFIS CLASSIFICATION METHOD ON PULSED RADAR TARGET CATEGORIZATION”. IU-Journal of Electrical & Electronics Engineering 6, no. 1 (January 2012): 97-105.
EndNote Avcı E, Turkoglu İ, Poyraz M (January 1, 2012) THE PERFORMANCE ANALYSIS OF STFT-ANFIS CLASSIFICATION METHOD ON PULSED RADAR TARGET CATEGORIZATION. IU-Journal of Electrical & Electronics Engineering 6 1 97–105.
IEEE E. Avcı, İ. Turkoglu, and M. Poyraz, “THE PERFORMANCE ANALYSIS OF STFT-ANFIS CLASSIFICATION METHOD ON PULSED RADAR TARGET CATEGORIZATION”, IU-Journal of Electrical & Electronics Engineering, vol. 6, no. 1, pp. 97–105, 2012.
ISNAD Avcı, Engin et al. “THE PERFORMANCE ANALYSIS OF STFT-ANFIS CLASSIFICATION METHOD ON PULSED RADAR TARGET CATEGORIZATION”. IU-Journal of Electrical & Electronics Engineering 6/1 (January 2012), 97-105.
JAMA Avcı E, Turkoglu İ, Poyraz M. THE PERFORMANCE ANALYSIS OF STFT-ANFIS CLASSIFICATION METHOD ON PULSED RADAR TARGET CATEGORIZATION. IU-Journal of Electrical & Electronics Engineering. 2012;6:97–105.
MLA Avcı, Engin et al. “THE PERFORMANCE ANALYSIS OF STFT-ANFIS CLASSIFICATION METHOD ON PULSED RADAR TARGET CATEGORIZATION”. IU-Journal of Electrical & Electronics Engineering, vol. 6, no. 1, 2012, pp. 97-105.
Vancouver Avcı E, Turkoglu İ, Poyraz M. THE PERFORMANCE ANALYSIS OF STFT-ANFIS CLASSIFICATION METHOD ON PULSED RADAR TARGET CATEGORIZATION. IU-Journal of Electrical & Electronics Engineering. 2012;6(1):97-105.
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