论文信息 - Microstrip filter design using FDTD and neural networks

Microstrip filter design using FDTD and neural networks

A new design technique using the FDTD method and neural networks is applied to a microstrip filter. The total design time is reduced by two means. First, an iterative ARMA signal estimation technique is utilized to reduce the computation time for each FDTD run. Second, the number of FDTD simulations is decreased with the use of the device model provided by a neural network with the ARMA coefficients at the output. The trained network was then incorporated to an optimization procedure for a microstrip filter design. © 2002 Wiley Periodicals, Inc. Microwave Opt Technol Lett 34: 219–224, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.10422

Eliathamby Ambikairajah | Rodica Ramer | Marian Gabriel Banciu

[1] Rodica Ramer,et al. Design of microstrip dual mode filters using finite-difference time-domain method , 2000, 2000 Asia-Pacific Microwave Conference. Proceedings (Cat. No.00TH8522).

[2] S. Prasad,et al. Reverse modeling of microwave circuits with bidirectional neural network models , 1998 .

[3] Martin A. Riedmiller,et al. A direct adaptive method for faster backpropagation learning: the RPROP algorithm , 1993, IEEE International Conference on Neural Networks.

[4] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .

[5] John W. Bandler,et al. Neuromodeling of microwave circuits exploiting space mapping technology , 1999, IMS 1999.

[6] G. L. Creech,et al. Artificial neural networks for fast and accurate EM-CAD of microwave circuits , 1997 .