1. Ljung, L., System Identification: Theory For
The User, Englewood Cliffs, NJ, Prentice Hall,
1987
2. Gauss, K. F., Theory of the Motion of Heavenly
Bodies, Dover, 1963.
3. Zadeh, L.A., “From Circuit Theory to System
Theory”, Proc IRE, 50, 856-865, 1962.
4. Töderstrom S., System Identification, Prentice-
Hall, 1989.
5. Ljung L., Söderström T., Theory and Practice Of
Recursive Identification, Cambridge, MA, MIT
Press, 1983.
6. Makhoul, J., “Linear Prediction: A Tutorial
Review”, Proc. IEEE, Cilt 63, 561-580, 1975.
7. Lim, Y.C., Parker, S.R., “On The Identification Of
Systems From Data Measurements Using ARMA
Lattice Models”, IEEE TRANS. ASSP, Cilt 4,
824-827, 1986.
8. Özer, Ş., Taşpınar, N., Güney, K., “ARMA modeli
ile Ayrık Zamanlı Lineer Sistemlerin
Modellenmesi”, Bilkent Üni. Elektrik-
Elektronik ve Bilgisayar Mühendisliği
Konferansı Bildiri kitabı, 195-198, 1991.
9. Özer, Ş., Sağıroğlu, Ş., “Kaplan, A., Performance
Analysis of Algorithms on Linear ARMA
Models”, Proc. Of the Int. Symposium
Computer and Information Science XVI, 445-
451, 2001.
10. Widrow, B, Stearns, D., Adaptive Signal
Processing, Prentice Hall, 1985.
11. Honig, H.L., Messerschmitt, D.G., Adaptive
Filters Structures, Algorithms and applications,
Kluwer Academic Publishers, 1984
12. Isidori A., “Nonlinear Control Systems: An
Introduction”, Lecture Notes in Control An
Information Science, Cilt 72, Springer-Verlag,
Berlin, 1985.
13. Prochazka, A., Neumann, R., “High Frequency
Distortion Analysis Of A Semiconductor Diode
For CATV Applications”, IEEE Trans. on
Consumer Electronics, Cilt CE-21, 120-129, 1975.
14. Nam, S.W., Powers, E.J., “Application Of Higher
Order Spectral Analysis To Cubically Nonlinear
System Identification”, IEEE Trans. on Signal
Processing, Cilt 42, 2124-2135, 1994.
15. Özgunel, S., Kayran, A. H., Panayirci, E.,
“Nonlinear Channel Equalization and
Identification”, Proc. Of Int. Conf. on Digital
Signal Proc., 260-265, Florence,1991.
16. Özden, M. T., Kayran, A. H., Panayirci, E.,
“Adaptive Volterra Filtering with Complete
Lattice Orthogonalization”, IEEE Trans. On
Signal Proc., Cilt 44, 2092-2098, 1996.
17. Griffith, D.W., Arce, G.R., “Partially Decoupled
Volterra Filters: Formulation and LMS
Adaptation”, IEEE Trans. on Signal Processing,
Cilt 45, 1485-1494, 1997.
18. Lee, J., Mathews, V.J., “A Stability Condition For
Certain Bilinear Systems”, IEEE Trans. on
Signal Processing, Cilt 42, 1871-1873, 1994.
19. Cowan, C.F, Grant, P.M., “Nonlinear System
Modelling - Concept and Application”,
Proceedings Of IEEE Int. Conference On
Acoustic Speech and Signal Processing, 1-4, San
Diego, California, 1984.
20. Priestley, M. B., Nonlinear and Non-Stationary
Time Series Analysis, Academic Press,1988.
21. Rauf, F., Nonlinear Adaptive Filtering : A
Unified Approach, Ph.D. Thesis, Boston
University, Boston, 1993.
22. Giannakis, G.B., Serpedin, E., “A Bibliography on
Nonlinear System Identification”, Signal
Processing, Cilt 81, 533-580, 2001.
23. Khurram, M. U., Fast Learning Nonlinear
Adaptive Filtering Structures, Ph.D. Thesis,
University Of Boston, 1994.
24. Koh, T., Powers, E. J., “Scond Order Volterra
Filtering and Its Application to nonlinear system
identification”, IEEE Trans. on ASSP, Cilt 33,
1445-1455, 1985.
25. Leuschen, M.L., Walker, I.D.; Cavallaro, J.R.;”
Fault residual generation via nonlinear analytical
redundancy”, IEEE Transactions on Control
Systems Technology, Cilt:13, 452-458, 2005.
26. Goldberger, AL., “Applications of chaos to
physiology and medicine”, In: Kim JH, Stringer
J, eds. Applied Chaos. New York: John Wiley &
Sons, 321-329, 1992.
27. Sağıroğlu, Ş., Özer, Ş., “A Neural Identifier for
Linear Dynamic Systems”, Journal of
Polytechnic, Cilt 4, 55-61, 2001.
28. Özer, Ş., Sağıroğlu Ş.,Zorlu H., “Arma Sistem
Modellemede Klasik ve Yapay Sinir Ağları
Algoritmalarının Karşılaştırılması”, Elektrik-
Elektronik-Bilgisayar Mühendisliği 10.Ulusal
Kongresi Bildiriler Kitabı, 434-437, 2003.
29. Narendra, K.S., Mukhopadhyay, S., “Adaptive
Control Using Neural Networks and Approximate
Models”, IEEE Trans. on Neural Networks, Cilt
8, 475-485, 1997.
30. Kaplan, A., Nümerik Tabu Arama Algoritması,
Doktora Tezi, Erciyes Üniversitesi, Kayseri, 2001
31. Wang, Z., Gu, H., “Parameter Identification of
Bilinear System Based on Genetic Algorithm”,
LNCS 4688, 83 – 91, 2007.
32. Karaboga, N., “Digital IIR Filter Design Using
Differential Evolution Algorithm”, EURASIP
Journal on Applied Signal Processing, Cilt 8,
1269–1276, 2005.
33. Cheng, S. L., Hwang, C., “Optimal approximation
of linear systems by a differential algorithm”,
IEEE Trans Syst Man and Cybernet—Part A
Syst Humans, Cilt 31, 698–707, 2001.
34. Chang, W.D., “Parameter identification of
Rossler’s chaotic system by an evolutionary
algorithm”, Chaos, Solitons and Fractals, Cilt
29, 1047–1053, 2006.
Doğrusal Olmayan Par Sistemler Kullanılarak Kaotik Zaman Serisi Kestirimi Ş. Özer ve H. Zorlu
Gazi Üniv. Müh. Mim. Fak. Der. Cilt 27, No 2, 2012 331
35. Chang, W.D., “Parameter identification of Chen
and Lü systems: A differential evolution
approach”, Chaos, Solitons and Fractals, Cilt 32,
1469–1476, 2007.
36. Price, K. V., An introduction to differential
evolution, in D. Corne, M. Dorigo, and F. Glover,
(Ed), New Ideas in Optimization, chapter 6,
McGraw Hill, London, UK, 1999.
37. Bağış, S., Yapay Zeka Algoritmaları
Kullanılarak Sistem Modelleme, Yüksek Lisans
Tezi, Erciyes Üniversitesi, Kayseri, 2009.
38. Kristinsson, K., Dumont, G.A., “System
Identification and Control using Genetic
Algorithms”, IEEE Trans. on Systems, Man,
and Cybernetics, Cilt 22-5, 1033-1046, 1992.
39. Pham, D.T., Karaboga, D., Intelligent
Optimisation Techniques: Genetic Algorithms,
Tabu Search, Simulated Annealing and Neural
Networks, Springer- Verlag, 2000.
40. Madar, J., Abonyi, J., Szeifert, F., “Genetic
Programming for the Identification of Nonlinear
Input−Output Models”, Ind. Eng. Chem. Res.,
Cilt 44-9, 3178-3186, 2005.
41. Bağış, A., Özçelik, Y., “Gerçek Kodlu Genetik
Algoritma Kullanılarak Sistem Kimliklendirme”,
12. Elektrik, Elektronik, Bilgisayar,
Biyomedikal Mühendisliği Ulusal Kongresi,
Eskişehir, 2007.
42. Bagis, A., “Performance Comparison of Genetic
and Tabu Search Algorithms for System
Identification”, Lecture Notes in Computer
Science (including subseries Lecture Notes in
Artificial Intelligence and Lecture Notes in
Bioinformatics), Cilt 4251 LNAI-I, 94-101, 2006.
43. Price, K., Storn, R., “Differential Evolution:
Numerical Optimization Made Easy”, Dr. Dobb’s
J., Cilt 78, 18–24, 1997.
44. Bağış, A., Özçelik, Y., “Farksal Evrim
Algoritması Kullanılarak Sistem Kimliklendirme”,
Otomatik Kontrol Ulusal Toplantısı (TOK’07),
178-183, İstanbul, 2007.
45. Hou, Z., “Wiener Model Identification based on
Adaptive Particle Swarm Optimization”,
Proceedings of the Seventh International
Conference on Machine Learning and
Cybernetics, 1041-1045, Kunming,12-15 July
2008.
46. Liu, L., Liu, W., Cartes, D.A., “Particle Swarm
Optimization based Parameter Identification
Applied to Permanent Magnet Synchronous
Motors”, Engineering Applications of Artificial
Intelligence, Cilt 21, 1092–1100, 2008.
47. Zorlu, H., Özer Ş., “Doğrusal Olmayan
Sistemlerin Klonal Seçme Algoritması
Kullanılarak Kimliklendirilmesi”, Sinyal İşleme
ve Uygulamaları Kurultayı (SİU), 2009.
48. Subudhi, B., Debashisha, J., “A Combined
Differential Evolution and Neural Network
Approach to Nonlinear System Identification”,
IEEE Region 10 Conference, TENCON 2008, 1-
6, 19-21 Nov. 2008.
49. Subudhi, B., Jena, D., Gupta, M.M., “Memetic
Differential Evolution Trained Neural Networks
for Nonlinear System Identification”, Third
International Conference on Industrial and
Information Systems (ICIIS’2008), 1-6, 2008.
50. Karaboğa, D., Yapay Zeka Optimizasyon
Algoritmaları, Atlas yayın dağıtım, İstanbul,
2004.
51. Holland, J.H., Adaption in Natural and
Artificial Systems, MAMIT Press, Cambridge,
1975.
52. De Castro, L.N., Von Zuben, F.J., “The clonal
selection algorithm with engineering
applications”, In Workshop Proceedings of
GECCO’00, Workshop on Artificial Immune
Systems and their Applications, 36–37, Las
Vegas, 2000.
53. De Castro, L.N., Von Zuben, F.J.: “Learning and
optimization using clonal selection principle”,
IEEE Transactions on Evolutionary
Computation, Special Issue on Artificial
Immune Systems, Cilt 6-3, 239–251, 2001.
54. Aslantas, V., Ozer, S., and Ozturk, S., “A Novel
Clonal Selection Algorithm Based Fragile
Watermarking Method”, LNCS, Cilt 4628, 358-
369, 2007.
55. Ada, G. L. and Nossal, G., “The clonal selection
theory”, Scientific American, Cilt 257, 50−57,
1987.
56. Lorenz, E.N., “Deterministic Nonperiodic Flow”,
Journal of the Athmosferic Sciences, Cilt 20,
130-141, 1963.
57. González, O.A., Han, G., de Gyvez, J.P., and
Edgar, “CMOS Cryptosystem Using a Lorenz
Chaotic Oscillator”, Proceedings of the IEEE
International Symposium on Circuits and
Systems, ISCAS '99, Cilt 5, 442-445, 1999.
58. Chen Y. A., Yang B. A., Dong J. A., Abraham A.,
“Time-Series Forecasting Using Flexible Neural
Tree Model”, Information Sciences, Cilt 174,
219–235, 2005.
59. Wang, L.X., Mendel, J.M., “Generating fuzzy
rules by learning from examples”, IEEE
Transactions on Systems, Man and
Cybernetics, Cilt 22, 1414–1427, 1992.
60. Cho, K.B., Wang, B.H., “Radial basis function
based adaptive fuzzy systems their application to
system identification and prediction”, Fuzzy Sets
and Systems, Cilt 83, 325–339, 1995.
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