A new method to improve the gain of patch antenna with metamaterial composed of ring aperture lattice is presented. The influences of the number of metamaterial layers and a comparison of electromagnetic characteristics between the conventional patch antenna and the new metamaterial patch antenna are studied by using numerical simulation method. Then, a patch antenna with the metamaterial is fabricated and measured. The simulation and experimental results show that this method is effective and this structure can realize congregating the radiation energy, thus the gain of the antenna with metamaterial can greatly increase when compared with the conventional one.

In this paper, a hybrid genetic algorithm for solving constrained optimization problems is addressed. First, a real-coded genetic algorithm is presented. The simplified quadratic interpolation method is then integrated into the genetic algorithm to improve its local search ability and the accuracy of the minimum function value. Simulation results on 13 benchmark problems show that the proposed hybrid algorithm is able to avoid the premature convergence and find much better solutions with high speed compared to other existing algorithms.

A folded slot with open end is introduced to achieve a dual-band coplanar waveguide (CPW)-fed monopole antenna for radio frequency identification (RFID) applications. The designed antenna, which, including the substrate, is only 32 mm in height and 20 mm in width, can operate simultaneously at the 2.45 and 5.8 GHz bands with -1.8 and 2.3 dBi gains, respectively. Its properties make the antenna suitable for RFID tags.

Adomian’s decomposition method (ADM) is a nonnumerical method which can be adapted for solving nonlinear ordinary differential equations. In this paper, the principle of the decomposition method is described, and its advantages as well as drawbacks are discussed. Then an aftertreatment technique (AT) is proposed, which yields the analytic approximate solution with fast convergence rate and high accurscy through the application of Padé approximation to the series solution derived from ADM. Some concrete examples are also studied to show with numerical results how the AT works efficiently.

An optimal allocation model for the subprocessing-element (sub-PE) level redundancy is developed, which is solved by the genetic algorithms. In the allocation model, the average defect density D and the parameter δ are also considered in order to accurately analyze the element yield, where δ is defined as the ratio of the support circuit area to the total area of a PE. When the PE’s area is imposed on the constraint, the optimal solutions of the model with different D and δ are calculated. The simulation results indicate that, for any fixed average defect density D, both the number of the optimal redundant sub-circuit added into a PE and the PE’s yield decrease as δ increases. Moreover, for any fixed parameter δ, the number of the optimal redundant sub-circuit increases, while the optimal yield of the PE decreases, as D increases.