科研成果 by Type: Conference Paper

Aiming at the requirement of miniaturization and high performance of antenna unit in MMW portable imaging system, a novel approach is presented to decrease the side lobe for millimeter wave applications using metamaterial (MTM) profile based antennas. The extraction of effective parameters of a metamaterial unit cell and its effect are also presented. The simulation results show that the side lobe of the proposed antenna is lower than -17dB at 35GHz.

The bubbles have a huge influence on the passive millimeter-wave (PMMW) radiation of ship wakes. The bubble distribution is able to be simulated based on the semi-empirical formula of Kelvin wake and turbulence energy attenuation spectrum. With the Maxwell-Garnett (MG) theory, the PMMW radiation of bubbles in different conditions can be calculated. Furthermore, the imaging experiment results are in a good agreement with the mathematical calculation results, which confirms the validity of the simulation model.

As recent trends in comparing the Han and Roman empires from primarily the point of view of literary evidence has brought forth new frameworks and opportunities of research, one asks how these developments could contribute to the comparison of the two empires' governance behaviors. The paper first surveys current literature published in the past decade and identify common themes in the scholarship on the Han and the Roman metallurgical advances and aspects of their iron industries. Of particular focus is the gradual awareness in the importance of iron semi-products in the Han and the Roman domains. In the second and third section, literary sources from the Qin-Han and the Roman domains are reviewed in order to identify general trends that can be juxtaposed for closer discussion. Particular emphasis is placed on the relationship between the private iron operators with generational legacies in the iron industries even be fore the formation of the Qin-Han and the Roman states, and how the state administrators engage with and adapt to the sophisticated and complex traditions of the Qin-Han and Roman iron industries. The fourth section provides a comparative discussion on issues concerning the states' juridical or statutory approaches to regulating iron mining and smelting operations, and observations on the intersect between semi-products, local ironworks andsmithies, and the needs of agricultural producers.

The traditional multiple audio objects codec extracts the parameters of each object in the frequency domain and produces serious confusion because of high coincidence degree in subband among objects. This paper uses sparse domain instead of frequency domain and reconstruct audio object using the binary mask from the down-mixed signal based on the sparsity of each audio object. In order to overcome high coincidence degree of subband among different audio objects, the sparse autoencoder neural network is established. On this basis, a multiple audio objects codec system is built up. To evaluate this proposed system, the objective and subjective evaluation are carried on and the results show that the proposed system has the better performance than SAOC.

In recent years, many researches focus on sound source localization based on neural networks, which is an appealing but difficult problem. In this paper, a novel time-domain end-to-end method for sound source localization is proposed, where the model is trained by two strategies with both cross entropy loss and mean square error loss. Based on the idea of multi-task learning, CNN is used as the shared hidden layers to extract features and DNN is used as the output layers for each task. Compared with SRP-PHAT, MUSIC and a DNN-based method, the proposed method has better performance.

In back-end analog/mixed-signal (AMS) design flow, well generation persists as a fundamental challenge for layout compactness, routing complexity, circuit performance and robustness. The immaturity of AMS layout automation tools comes to a large extent from the difficulty in comprehending and incorporating designer expertise. To mimic the behavior of experienced designers in well generation, we propose a generative adversarial network (GAN) guided well generation framework with a post-refinement stage leveraging the previous high-quality manually-crafted layouts. Guiding regions for wells are first created by a trained GAN model, after which the well generation results are legalized through post-refinement to satisfy design rules. Experimental results show that the proposed technique is able to generate wells close to manual designs with comparable post-layout circuit performance.