Review of artificial neural networks applications in microwave computer-aided design

International Journal of RF and Microwave Computer-Aided Engineering

Volumn 9, Issue 3, 1999, Pages 158-174

  Burrascano, P ^a,b   Fiori, S ^a,c   Mongiardo, M ^{a,b,d,e,f,g,h,i,j}  

^a UNIVERSITY OF PERUGIA   (Italy)

^b SAPIENZA UNIVERSITY OF ROME   (Italy)

^c UNIVERSITÀ POLITECNICA DELLE MARCHE   (Italy)

^d UNIVERSITY OF ROME TOR VERGATA   (Italy)

^e UNIVERSITY OF BATH   (United Kingdom)

^f UNIVERSITY OF PALERMO   (Italy)

^g Technical Program Committee   (Italy)

^h UNIVERSITY OF VICTORIA   (Canada)

ⁱ University of Corvallis   (United States)

^j UNIVERSITY OF MUNICH   (Germany)

more..

Author keywords

[No Author keywords available]

Indexed keywords

SELF-ORGANIZING MAPS;

COMPUTER AIDED DESIGN; ELECTRIC NETWORK SYNTHESIS; MICROWAVE CIRCUITS; NEURAL NETWORKS;

MICROWAVE FILTERS;

EID: 0032641444     PISSN: 10964290     EISSN: None     Source Type: Journal    
DOI: 10.1002/(SICI)1099-047X(199905)9:3<158::AID-MMCE3>3.0.CO;2-V     Document Type: Article

References (51)

1. J. Carroll and K. Chang, Statistical computer-aided design for microwave circuits, IEEE Trans Microwave Theory Tech 44 (1996), 24-32.
2. M. Mongiardo, Sensitivity evaluations of microwave filters by the adjoint network method, MTT-S, Workshop State of the art filter design using EM and circuit simulation techniques, Denver, CO, 1997, invited.
3. M. Mongiardo, Sensitivity calculations of waveguiding structures: applications and comparison of solutions, Microwave and RF, London, U.K., 1996, invited.
4. M. Mongiardo and R. Ravanelli, Automated design of corrugated feeds by the adjoint network method, IEEE Trans Microwave Theory Tech 1997.
5. F. Alessandri, M. Dionigi, M. Mongiardo, and R. Sorrentino, Fullwave optimization and sensitivity of waveguide networks: a comparison of approaches, Int J MIMICAE (1997).
6. F. Alessandri, M. Mongiardo, and R. Sorrentino, New efficient full wave optimization of microwave circuits by the adjoint network method, IEEE Microwave Guided Wave Lett 3 (1993), 414-416.
7. J. Bandler, R. Biernacki, S. Chen, R. Hemmers, and K. Madsen, Electromagnetic optimization exploiting aggressive space mapping, IEEE Trans Microwave Theory Tech 43 (1995), 2874-2882.
8. J. Bandler, R. Biernacki, and S. Chen, Fully automated space mapping optimization of 3D structures, Int Microwave Symp Dig, 1996, pp. 753-756.
9. J. Bandler, R. Biernacki, S. Chen, and Y. Huang, Design optimization of interdigital filters using aggressive space mapping and decomposition, IEEE Trans Microwave Theory Tech 45 (1997).
10. J. Bandler, R. Biernacki, S. Chen, and D. Omeragic, Space mapping optimization of waveguide filters using finite element and mode-matching electromagnetic simulators, Int Microwave Symp Dig, 1997.
11. Artificial neural networks applications, IEEE Proc 84 (1996), special issue.
12. W.S. McCulloch and W. Pitts, A logical calculus of the ideas immanent in nervous activity, Bull Math Biophys 5 (1943), 115-133.
13. D.O. Hebb, The organization of behavior, Wiley, New York, 1970.
14. F. Rosenblatt, The perceptron: a probabilistic model for information storage and organization in the brain, Psychol Rev (1958), 386-408.
15. J. Hopfield, Neural networks and physical system with emergent collective computational properties, Proc Natl Acad Sci USA (1982), 2554-2558.
16. D. Rumelhart, G. Hinton, and R.J. Williams, "Learning internal representations by error propagation," Parallel distributed processing: Explorations in the microstructure of cognition, Ch. 8. Foundations, Vol. 1, MIT Press, Cambridge, MA, 1986, pp. 318-362.
17. A. Wieland and R. Leighten, Geometric analysis of neural network capacity, Proc IEEE first ICNN, Vol. 6, 1987, pp. 385-392.
18. B. Irie and S. Miyake, Capacity of three layered perceptrons, Proc IEEE ICNN 1, Vol. 7, 1988, pp. 641-648.
19. S.M. Carrol and B.W. Dickinson, Construction of neural nets using radon transform, Proc IJCNN, Vol. 1, 1989, pp. 607-611.
20. K. Hornik, M. Stichcombe, and H. White, Multilayer feedforward networks are universal approximators, Neural Networks 2 (1989), 359-366.
21. G. Cybenko, Approximation by superpositions of a sigmoidal function, Math Contr Signals Syst 2 (1989), 303-314.
22. C. Stone, Optimal global rates of convergence for non-parametric regression, Ann Stat 10 (1982), 1040-1053.
23. H. Akaike, A new look at the statistical model identification, IEEE Trans Automat Contr 19 (1974), 716-723.
24. J. Rissanen, Stochastic complexity and modelling, Ann Statist 14 (1986), 1080-1100.
25. D. Rumelhart, G. Hinton, and R.J. Williams, "The effective number of parameters: an analysis of generalisation and regularization in nonlinear learning systems," Advances in neural information processing systems, J. Moody, S. Hanson, and R. Lippmann (Editors), Morgan Kaufmann, Cambridge, MA, 1992, pp. 318-362.
26. S. Amari, N. Murata, and S. Yoshizawa, A criterion for determining the number of parameters in an artificial neural model, Proc Int Conf Artificial Neural Networks 1991, pp. 9-14.
27. D.B. Fogel, An information criterion for optimal neural network selection, IEEE Trans Neural Networks 2 (1991), 490-497.
28. N. Murata, S. Yoshizawa, and S. Amari, Network information criterion - determining the number of hidden units for an artificial neural network, METR 92-05, Technical Report, University of Tokyo, 1992.
29. K. Yoshitomi, A. Ishimaru, J. Hwang, and J.S. Chen, Surface roughness determination using spectral correlations of scattered intensities and an artificial neural network technique, IEEE Trans Antennas Propagat 41 (1993), 498-502.
30. H. Southall, J.A. Simmers, and T. O'Donnell, Direction finding in phased arrays with a neural network beamformer, IEEE Trans Antennas Propagat 43 (1995), 1369-1374.
31. G. Washington, Aperture antenna shape prediction by feedforward neural networks, IEEE Trans Antennas Propagat 45 (1997), 683-688.
32. A. Patnaik, R.K. Mishra, G.K. Patra, and S.K. Dash, An artificial neural network model for effective dielectric constant of microstrip line, IEEE Trans Antennas Propagat 45 (1997), 1697.
33. M. Vai and S. Prasad, Automatic impedance matching with a neural network, IEEE Microwave Guided Wave Lett 3 (1993), 353-354.
34. M. Vai and S. Prasad, Microwave circuit analysis and design by a massively distributed computing network, IEEE Trans Microwave Theory Tech 43 (1995), 1087-1094.
35. T. Horng, C. Wang, and N.G. Alexopoulos, Microstrip circuit design using neural networks, Int Microwave Symp Dig, 1993, pp. 413-416.
36. P. Watson and K. Gupta, EM-ANN models for via interconnects in microstrip circuits, Int Microwave Symp Dig, 1996, pp. 1819-1822.
37. P. Watson and K. Gupta, EM-ANN models for microstrip vias and interconnects in multilayer circuits, IEEE Trans Microwave Theory Tech 44 (1996), 2495-2503.
38. P. Watson and K. Gupta, EM-ANN modeling and optimal chamfering of 90° cpw bends with airbridges, Int Microwave Symp Dig, 1997.
39. P. Watson and K. Gupta, Design and optimization of cpw circuits using EM-ANN models for CPW components, IEEE Trans Microwave Theory Tech 45 (1997), 2515-2523.
40. G.L. Creech, B. Paul, C. Lesniak, T. Jenkins, R. Lee, and M. Calcatera, Artificial neural networks for accurate microwave CAD applications, IEEE Int Microwave Symp Dig, 1996, pp. 733-736.
41. G.L. Creech, B. Paul, C. Lesniak, T. Jenkins, and M. Calcatera, Artificial neural networks for fast and accurate EM-CAD of microwave circuits, IEEE Trans Microwave Theory Tech 45 (1997), 794-802.
42. K. Shirakawa, M. Shimiz, N. Okubo, and Y. Daido, A large signal characterization of an HEMT using a multilayered neural network, IEEE Trans Microwave Theory Tech 45 (1997), 1630-1633.
43. A.H. Zaabab, Q.J. Zhang, and M.S. Nakhla, Neural network modeling approach to circuit optimization and statistical design, IEEE Trans Microwave Theory Tech 43 (1995), 1349-1358.
44. A.H. Zaabab, Q.J. Zhang, and M.S. Nakhla, Device and circuit-level modeling using neural networks with faster training based on network sparsity, IEEE Trans Microwave Theory Tech 45 (1997), 1696-11704.
45. F. Wang and Q. Zhang, Knowledge based neural models for microwave design, IEEE Int Microwave Symp Dig, 1997.
46. F. Wang and Q. Zhang, Knowledge based neural models for microwave design, IEEE Trans Microwave Theory Tech 45 (1997), 2333-2343.
47. A. Veluswami, M.S. Nakhla, and Q.J. Zhang, The application of neural networks to em-based simulation and optimization of interconnects in high-speed VLSI circuits, IEEE Trans Microwave Theory Tech 45 (1997), 712-723.
48. P. Burrascano, M. Dionigi, C. Fancelli, and M. Mongiardo, A neural network model for CAD and optimization of microwave filters, Int Microwave Symp Dig, 1998, pp. 13-16.
49. A. Caproni, F. Cervelli, M. Mongiardo, L. Tarricone, and F. Malucelli, Bandwidth reduced fullwave simulation of planar microstrip circuits, ACES Special Issue, 13 (1998), 197-204.
50. T. Kohonen, Clustering, taxonomy, and topological maps of patterns, Proc of the VI Int Conf on Pattern Recognition, 1982.
51. P. Watson, K. Gupta, and R.L. Mahajan, Development of knowledge based artificial neural network models for microwave components, Int Microwave Symp Dig, 1998, pp. 9-12.