In this paper, a novel multilayer substrate integrated waveguide (SIW) four-way out-of-phase power divider is proposed. It is realized by 3D mode coupling, on multilayer substrates. The structure consists of vertical Y-junction, lateral T-junction of SIW and lateral Y-junction of half-mode SIW. The advantages of the proposed structure are its low cost and ease of fabrication. Also, it can be integrated easily with other planar circuits such as microstrip circuits. An experimental circuit is designed and fabricated using the traditional printed circuit board technology. The simulated and measured results show that the return loss of the input port is above 15 dB over 8 to 11.8 GHz and transmissions are about -7.6±1.6 dB in the passband. It is expected that the proposed the proposed power divider will play an important role in the future integration of compact multilayer SIW circuits and systems.

Restoration is an important area in improving the visual quality, and lays the foundation for accurate object detection or terrain classification in image analysis. In this paper, we introduce Beta process priors into hierarchical sparse Bayesian learning for recovering underlying degraded hyperspectral images (HSI), including suppressing the various noises and inferring the missing data. The proposed method decomposes the HSI into the weighted summation of the dictionary elements, Gaussian noise term and sparse noise term. With these, the latent information and the noise characteristics of HSI can be well learned and represented. Solved by Gibbs sampler, the underlying dictionary and the noise can be efficiently predicted with no tuning of any parameters. The performance of the proposed method is compared with state-of-the-art ones and validated on two hyperspectral datasets, which are contaminated with the Gaussian noises, impulse noises, stripes and dead pixel lines, or with a large number of data missing uniformly at random. The visual and quantitative results demonstrate the superiority of the proposed method.