In this article, neural networks are employed for fast and efficient calculation of Green's functions in a layered medium. Radial basis function networks (RBFNs) are effectively trained to estimate the coefficients and the exponents that represent a Green's function in the discrete complex image met
Fast and efficient calculation of the multilayered shielded Green's functions employing neural networks
✍ Scribed by Juan Pascual García; David Cañete Rebenaque; Fernando D. Quesada Pereira; Jose L. Gómez Tornero; Alejandro Alvarez Melcón
- Publisher
- John Wiley and Sons
- Year
- 2004
- Tongue
- English
- Weight
- 313 KB
- Volume
- 44
- Category
- Article
- ISSN
- 0895-2477
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✦ Synopsis
In this paper, neural networks are used to efficiently calculate the multilayered media boxed Green's functions needed in integral equation (IE) formulations. The analysis of complex multilayered shielded circuits is computationally time consuming, due to the need to calculate the multilayered-media boxed Green's functions. Using neural networks as radial basis function networks, the boxed Green's functions can be calculated quickly, thus greatly reducing the computational time associated with the analysis of practical circuits. Once the neural network is trained with a known set of pairs of inputs and outputs, new outputs are quickly calculated, thus increasing the efficiency of the IE method.
📜 SIMILAR VOLUMES
## Abstract An efficient scheme is presented to calculate the periodic structure in planar multilayered media. The slowly converging series for the periodic Green's function is accelerated using the Ewald's method combined with Shank transformation and the computational time is significantly reduce