Design of Microstrip Low-Pass Filter Based on Six-Slit-Ring DGS
A novel six-slit-ring defected ground structure (DGS) is presented in this paper. The location of the slit can shift the resonant frequency without changing the overall size of the DGS and its adjustment range can reach 8.81 GHz. By cascading three identical six-slit-ring DGS unit cells, a microstrip low-pass filter (LPF) can be realized. Its 3dB cutoff frequency is 7.27 GHz. The in-band insertion loss is below 0.35 dB and the stop-band width with 20 dB attenuation is over 8.12 GHz. To improve the out-of-band rejection of the filter, shunt branches were added on both sides of the microstrip line. Its 3 dB cutoff frequency is 8.285 GHz. The insertion loss is less than 0.81dB in the pass-band. The stop-band rejection is better than -40 dB at 11.36-20 GHz and the size of the filter is only 28 mm by 11 mm. The simulation results show that the proposed novel six-slit-ring DGS microstrip LPF has the characteristics of compact size, flexible adjustment, flat pass-band, wide stop-band and high selectivity.
Novel DGS microstrip low-pass filter
A conventional microstrip low-pass filter has a large area and a narrow stop-band.To solve this problem,a new microstrip low-pass filter is presented in this paper,which is composed of semicircle defected ground structures and semicircle stepped-impedance shunt stubs.The effect of parameter variation of S-DGS and S-SISS on band-stop characteristic is studied.An equivalent circuit model of the proposed LPF is also described.The proposed filter is compact and the 3 dB cutoff frequency is 2.7 GHz.The stop-band is 4~16 GHz,which is wider by 20% than that of the conventional DGS filter.Simulation results are in good agreement with the measured results,which verifies the reliability of the designed filter.
Multi-directional spatial error concealment using adaptive edge thresholding
In this paper, a new method for spatial concealment of missing areas in image and video signals transmitted over error prone infrastructures, is presented. The concealment process is performed in three steps. First, a novel technique is used to estimate the significant edges of missing areas after performing a directional edge analysis on the correctly received neighboring blocks of the missing areas. This technique uses the moments of the neighboring edge magnitudes to obtain an adaptive threshold for rejecting non-significant directions. Second, based on the predicted significant directions, an approximation is obtained for each missing pixel. Finally, for each pixel, we compute a weighted average by using two edge correspondence measures as weighting factors. Moreover, the adaptive thresholding of the edges let us include as many edges as necessary in the interpolation process. Experiments show that the proposed method outperforms the previous state of the art methods based on both subjective and objective measures.