Yukinori Sasaki

Optimum design of balanced SAW filters using multi-objective differential evolution

Three Multi-Objective Differential Evolutions (MODEs) that differ in their selection schemes are applied to a real-world application, i.e., the multi-objective optimum design of the balanced Surface Acoustic Wave (SAW) filter used in cellular phones. In order to verify the optimality of the Pareto-optimal solutions obtained by the best MODE, those solutions are also compared with the solutions obtained by the weighted sum method. Besides, from the Principal Component Analysis (PCA) of the Pareto-optimal solutions, an obvious relationship between the objective function space and the design parameter space is disclosed.

Adaptive Application of Autoregressive Moving Average Method in Accelerating FDTD Simulation

The autoregressive moving average (ARMA) method is used to speed up the finite difference time domain (FDTD) simulation. Adaptive technique proposed as adaptive s- parameter method, is applied for the selection of ARMA model parameters, specifically the selection of training sequence. It is shown that the proposed method is more practically useful in that it is not model-dependent. It has made the signal predictor more stable and feasible for general-purpose use in combined FDTD simulation and signal processing.