01 Dec 2023
| 01 Dec 2023
Generating AI modules for decoupling capacitor placement using simulation
Related authors
Adv. Radio Sci., 21, 77–87, 2023
Adv. Radio Sci., 21, 37–48, 2023
Adv. Radio Sci., 15, 93–97, 2017
Adv. Radio Sci., 14, 77–83, 2016
Cited articles
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G. S., Davis, A., Dean, J., Devin, M., Ghemawat, S., Goodfellow, I., Harp, A., Irving, G.,Isard, M., Jozefowicz, R., Jia, Y., Kaiser, L., Kudlur, M., Levenberg, J., Mané, D., Schuster, M., Monga, R., Moore, S., Murray, D., Olah, C., Shlens, J., Steiner, B., Sutskever, I., Talwar, K., Tucker, P., Vanhoucke, V., Vasudevan, V., Viégas, F., Vinyals, O., Warden, P., Wattenberg, M., Wicke, M., Yu, Y., and Zheng, X.: TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems, https://www.tensorflow.org/ (last access: 12 September 2023), 2015. a
Cecchetti, R., de Paulis, F., Olivieri, C., Orlandi, A., and Buecker, M.: Effective PCB Decoupling Optimization by Combining an Iterative Genetic Algorithm and Machine Learning, Electronics, 9, 1243, https://doi.org/10.3390/electronics9081243, 2020. a
Chollet, F.: Keras, https://github.com/fchollet/keras (last access: 12 September 2023), 2015. a
Choy, D., Bartels, T., Stube, B., and Bruening, R.: A Contribution to the Treatment of Power Integrity Design Tasks using Reinforcement Learning, Adv. Radio Sci., 20, this issue, 2023. a
Franz, J.: EMV, Springer Fachmedien Wiesbaden GmbH, https://doi.org/10.1007/978-3-8348-2211-6, 2013. a
