Xidian University

About: Xidian University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Antenna (radio) & Computer science. The organization has 32099 authors who have published 38961 publications receiving 431820 citations. The organization is also known as: University of Electronic Science and Technology at Xi'an & Xīān Diànzǐ Kējì Dàxué.

Discriminative Dictionary Learning With Common Label Alignment for Cross-Modal Retrieval

Abstract: Cross-modal retrieval has attracted much attention in recent years due to its widespread applications. In this area, how to capture and correlate heterogeneous features originating from different modalities remains a challenge. However, most existing methods dealing with cross-modal learning only focus on learning relevant features shared by two distinct feature spaces, therefore overlooking discriminative feature information of them. To remedy this issue and explicitly capture discriminative feature information, we propose a novel cross-modal retrieval approach based on discriminative dictionary learning that is augmented with common label alignment. Concretely, a discriminative dictionary is first learned to account for each modality, which boosts not only the discriminating capability of intra-modality data from different classes but also the relevance of inter-modality data in the same class. Subsequently, all the resulting sparse codes are simultaneously mapped to a common label space, where the cross-modal data samples are characterized and associated. Also in the label space, the discriminativeness and relevance of the considered cross-modal data can be further strengthened by enforcing a common label alignment. Finally, cross-modal retrieval is performed over the common label space. Experiments conducted on two public cross-modal datasets show that the proposed approach outperforms several state-of-the-art methods in term of retrieval accuracy.

Design and Synthesis of Multilayer Frequency Selective Surface Based on Antenna-Filter-Antenna Using Minkowski Fractal Structures

Abstract: A multilayer frequency selective surface (FSS) with subwavelength fractal elements based on the antenna-filter- antenna (AFA) concept is proposed in this paper. The upper fractal patches are inductive and non-resonant, and the fractal slots on the ground provide a capacitance. The thin substrate is equivalent to a transformer and some resonant modes are produced. Multiple transmission poles are obtained by cascading multilayer two-dimensional periodic structure array of the fractal patches and slots on the ground. The cell periods along $x$ and $y$ directions are the same and the total height is 8 mm, and the fractional bandwidth reaches 30% at normal incidence. To analyze and understand the operating mechanism of the FSS, the equivalent circuit model (ECM) is proposed to analyze the transmission and reflection characteristics. The results of the synthesis from ECM agree well with the results of full-wave simulation. The multilayer AFA-FSS has been manufactured and measured to verify the effectiveness and correctness of the design and synthesis. The simulated results are in good agreement with the tested ones.

Robust Deadlock Control for Automated Manufacturing Systems With Unreliable Resources Based on Petri Net Reachability Graphs

Abstract: Resource failures may happen in automated manufacturing systems (AMSs) because of different reasons in the real world, making most existing deadlock control policies unapplicable. This paper develops methods for the robust deadlock control of AMSs with unreliable resources based on Petri nets. The considered AMSs are modeled with generalized systems of simple sequential processes with resources (GS3PR). First, a method based on reachability graph partition technique is provided to analyze the robust legal markings and the forbidden ones in an unreliable GS3PR (U-GS3PR), in which resource failures and recovery procedures are modeled with recovery subnets. Then, the control problem for such a system is converted into a problem for controlling the forbidden states in a U-GS3PR and control places can be designed by solving the maximal number of forbidden markings problems. Since the robust legal reachability spaces computed may be nonconvex and such a system cannot be optimally controlled by the conjunctions of linear constraints, we propose an interval-inhibitor-arc-based robust deadlock control policy for a system with nonconvex legal reachability spaces by solving the maximal number of ${t_{q}}$ -critical marking/transition separation instances problems (MNTMPs( ${t_{q}}$ )). Finally, examples are presented to demonstrate the proposed methods.

A Non-Greedy Algorithm for L1-Norm LDA

Abstract: Recently, L1-norm-based discriminant subspace learning has attracted much more attention in dimensionality reduction and machine learning However, most existing approaches solve the column vectors of the optimal projection matrix one by one with greedy strategy Thus, the obtained optimal projection matrix does not necessarily best optimize the corresponding trace ratio objective function, which is the essential criterion function for general supervised dimensionality reduction In this paper, we propose a non-greedy iterative algorithm to solve the trace ratio form of L1-norm-based linear discriminant analysis We analyze the convergence of our proposed algorithm in detail Extensive experiments on five popular image databases illustrate that our proposed algorithm can maximize the objective function value and is superior to most existing L1-LDA algorithms

Graphene/Organic Semiconductor Heterojunction Phototransistors with Broadband and Bi-directional Photoresponse.

Abstract: A graphene-semiconductor heterojunction is very attractive for realizing highly sensitive phototransistors due to the strong absorption of the semiconductor layer and the fast charge transport in the graphene. However, the photoresponse is usually limited to a narrow spectral range determined by the bandgap of the semiconductor. Here, an organic heterojunction (C60 /pentacene) is incorporated on graphene to realize a broadband (405-1550 nm) phototransistor with a high gain of 5.2 × 105 and a response time down to 275 µs. The visible and near-infrared parts of the photoresponsivity (9127 A W-1 @650 nm and 1800 A W-1 @808 nm) come from the absorption of the organic layer and the graphene, respectively. For the first time, a bi-directional (positive and negative) photoresponse is demonstrated at different wavelengths, due to the opposite charge transfer direction of the photoexcited carriers enforced by the unique band alignment. Such tunability will enable new functionalities such as large-scale real-time optical image and infrared focal plane array detection in the future.