An iterative optimization for decoupling capacitor placement on a power delivery network\n(PDN) is presented based on Genetic Algorithm (GA) and Artificial Neural Network (ANN). TheANN\nis first trained by an appropriate set of results obtained by a commercial simulator. Once the ANN is\nready, it is used within an iterative GA process to place a minimum number of decoupling capacitors\nfor minimizing the differences between the input impedance at one or more location, and the required\ntarget impedance. The combined GAâ??ANN process is shown to effectively provide results consistent\nwith those obtained by a longer optimization based on commercial simulators. With the new approach\nthe accuracy of the results remains at the same level, but the computational time is reduced by at least\n30 times. Two test cases have been considered for validating the proposed approach, with the second\none also being compared by experimental measurements.
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