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A Miniaturized Bandwidth Reconfigurable Bandpass Chip Filter with Semi-lumped Topology and GaAs pHEMT Technology

Chinese Journal of Electronics 2021年第1期30卷 192-198页

作者： LI Linqing ZHU Haoran NING Xingyu LI Zunwen WU Xianliang Key Lab of Intelligent Computing and Signal Processing Ministry of Education Anhui University

A miniaturized reconfigurable bandpass chip filter with semi-lumped topology and Gallium Arsenide pseudomorphic High electron mobility transistor（GaAs pHEMT） technology is proposed. Semi-lumped topology is employed to instead the traditional lumped inductor with microstrip transmission line, which can reduced the size of the tunable filter significantly. Three-order series and shunt resonated bandpass filter is implemented with shorted stubs and metal-insulator-metal capacitors. Two transmission zeros are introduced with the series resonator and the shunted GaAs FET. By tuning the gate bias circuit of the FET, the capacitance of the series resonator is changed and the bandwidth of the filter is adjusted correspondingly. An equivalent circuit model is developed to interpret the mechanism of the proposed filter circuit. A reconfigurable on chip filter sample operated at 10 GHz is fabricated to validate the design. Two fractional bandwidth of 14.3% and 23.5% are tuned with bias voltage of the FET, while insertion loss of 2.4 d B and 2.2 d B are observed with the filter, respectively. The area of the chip filter is 0.86 × 0.96 mm2and is equivalent to an electrical length of 0.08 × 0.09λg2at center frequency. Measurement results agree well with the simulation ones.

关键词： gallium arsenide tunable filter transmission zeros equivalent circuit model resonator filters shunted FET III-V semiconductors miniaturized bandwidth reconfigurable bandpass chip filter MIM devices microstrip transmission line chip filter sample shunt resonated bandpass filter metal-insulator-metal capacitors semilumped topology loss 2.4 dB Gallium Arsenide pseudomorphic High electron mobility transistor technology insertion loss filter circuit integrated circuit design GaAs integrated circuit manufacture frequency 10.0 GHz pHEMT technology microwave filters loss 2.2 dB HEMT integrated circuits series resonator miniaturized reconfigurable bandpass chip filter band-pass filters

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Hierarchical Covering Algorithm

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Tsinghua Science and Technology 2014年第1期19卷 76-81页

作者： Jie Chen Shu Zhao Yanping Zhang Department of Computer Science and Technology and Key Lab of Intelligent Computing and Signal Processing Anhui University

The concept of deep learning has been applied to many domains, but the definition of a suitable problem depth has not been sufficiently explored. In this study, we propose a new Hierarchical Covering Algorithm （HCA） method to determine the levels of a hierarchical structure based on the Covering Algorithm （CA）. The CA constructs neural networks based on samples＇ own characteristics, and can effectively handle multi-category classification and large-scale data. Further, we abstract characters based on the CA to automatically embody the feature of a deep structure. We apply CA to construct hidden nodes at the lower level, and define a fuzzy equivalence relation R on upper spaces to form a hierarchical architecture based on fuzzy quotient space theory. The covering tree naturally becomes from R. HCA experiments performed on MNIST dataset show that the covering tree embodies the deep architecture of the problem, and the effects of a deep structure are shown to be better than having a single level.

关键词： deep architecture hierarchy fuzzy equivalence relation covering tree MNIST dataset

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MICkNN:Multi-Instance Covering kNN Algorithm

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Tsinghua Science and Technology 2013年第4期18卷 360-368页

作者： Shu Zhao Chen Rui Yanping Zhang Department of Computer Science and Technology and Key Lab of Intelligent Computing and Signal Processing Anhui University

Mining from ambiguous data is very important in data mining. This paper discusses one of the tasks for mining from ambiguous data known as multi-instance problem. In multi-instance problem, each pattern is a labeled bag that consists of a number of unlabeled instances. A bag is negative if all instances in it are negative. A bag is positive if it has at least one positive instance. Because the instances in the positive bag are not labeled, each positive bag is an ambiguous. The mining aim is to classify unseen bags. The main idea of existing multi-instance algorithms is to find true positive instances in positive bags and convert the multi-instance problem to the supervised problem, and get the labels of test bags according to predict the labels of unknown instances. In this paper, we aim at mining the multi-instance data from another point of view, i.e., excluding the false positive instances in positive bags and predicting the label of an entire unknown bag. We propose an algorithm called Multi-Instance Covering kNN （MICkNN） for mining from multi-instance data. Briefly, constructive covering algorithm is utilized to restructure the structure of the original multi-instance data at first. Then, the kNN algorithm is applied to discriminate the false positive instances. In the test stage, we label the tested bag directly according to the similarity between the unseen bag and sphere neighbors obtained from last two steps. Experimental results demonstrate the proposed algorithm is competitive with most of the state-of-the-art multi-instance methods both in classification accuracy and running time.

关键词： mining ambiguous data multi-instance classification constructive covering algorithm kNN algorithm

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Multiple-Instance Learning with Instance Selection via Constructive Covering Algorithm

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Tsinghua Science and Technology 2014年第3期19卷 285-292页

作者： Yanping Zhang Heng Zhang Huazhen Wei Jie Tang Shu Zhao the Department of Computer Science and Technology and Key Lab of Intelligent Computing and Signal Processing Anhui University the Department of Computer Science and Technology and Key Lab of Intelligent Computing and Signal Processing Anhui University1Hefei 230601 China the Department of Computer Science and Technology Tsinghua University

Multiple-Instance Learning （MIL） is used to predict the unlabeled bags＇ label by learning the labeled positive training bags and negative training *** bag is made up of several unlabeled instances.A bag is labeled positive if at least one of its instances is positive,otherwise *** multiple-instance learning methods with instance selection ignore the representative degree of the selected *** example,if an instance has many similar instances with the same label around it,the instance should be more representative than *** on this idea,in this paper,a multiple-instance learning with instance selection via constructive covering algorithm （MilCa） is *** MilCa,we firstly use maximal Hausdorff to select some initial positive instances from positive bags,then use a Constructive Covering Algorithm （CCA） to restructure the structure of the original instances of negative *** an inverse testing process is employed to exclude the false positive instances from positive bags and to select the high representative degree instances ordered by the number of covered instances from training ***,a similarity measure function is used to convert the training bag into a single sample and CCA is again used to classification for the converted *** results on synthetic data and standard benchmark datasets demonstrate that MilCa can decrease the number of the selected instances and it is competitive with the state-of-the-art MIL algorithms.

关键词： multiple-instance learning instance selection constructive covering algorithm maximal Hausdorff

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Joint relay selection and power allocation protocol for two-way relaying system

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International Journal of Wireless and Mobile computing 2019年第4期17卷 349-360页

作者： Zhi, Hui Zhu, Jun Hu, Yanjun Key Lab of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei Anhui230601 China

The Joint Relay Selection and Power Allocation (JRSPA) for Amplify-and-Forward (AF) relaying (JRSPA-AF) combines Power Allocation (PA) and Relay Selection (RS) very well in Two- Way Relaying (TWR) system. In order to explore the system performance of JRSPA-AF protocol, the outage probability and Diversity-Multiplexing Trade-off (DMT) of JRSPA-AF protocol are analysed. One upper bound, two lower bounds and approximate expressions of outage probability along with the DMT are derived. Based on this, the idea of JRSPA is introduced into Decode-and- Forward (DF) relaying TWR system, and the JRSPA-DF protocol is proposed. Moreover, the exact expressions of outage probability and DMT for JRSPA-DF are derived. Simulations are developed to validate the analytical results, the results show that the approximation outage probability of JRSPA-AF can be used well to evaluate system outage probability over the entire transmission SNR region, and the analysis results of outage probability of JRSPA-DF are consistent with its simulation results. In addition, the simulation results indicate that JRSPA-DF can achieve lower outage probability than JRSPA-AF and other protocols. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Probability

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A Full-Rate and Low-Detection Complexity Cooperative Transmission Scheme Based on Distributed Space-Time-Frequency Code Design

A Full-Rate and Low-Detection Complexity Cooperative Transmi...

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2013 IEEE 4th International Conference on Software Engineering and Service Science

作者： Hongyu Fang Ruzi Li Li Wang Xiaohui Li Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University

ISBN: (纸本)9781467349994

The cooperative transmission schemes based on the amplify and forward（AF） mode have the defect of low transmission rate and the exiting full-rate cooperative transmission schemes based on space-time code design have the defect of high detection ***,this paper makes the best of linear constellation precoding（LCP） technique and cyclic delay diversity（CDD） technique,and adopts the nonorthogonal amplify and forward（NAF） mode,finally proposes a new full-rate wireless cooperative transmission scheme based on space-time-frequency code *** with the cooperative transmission schemes that only pursue the transmission rate or the BER performance,this new scheme can apply to multi-relay scenario,and has the advantages of simple structure,low signal detection complexity that does not increases with the number of relay *** of above makes the real-time data transmission service of high quality come to be possible.

关键词： cooperative space-time-frequency full-rate lowdetection complexity

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DMFVAE:miRNA-disease associations prediction based on deep matrix factorization method with variational autoencoder

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Frontiers of Computer Science 2024年第6期18卷 259-270页

作者： Pijing WEI Qianqian WANG Zhen GAO Ruifen CAO Chunhou ZHENG Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information TechnologyAnhui UniversityHefei 230601China Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and TechnologyAnhui UniversityHefei 230601China Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial IntelligenceAnhui UniversityHefei 230601China

MicroRNAs(miRNAs)are closely related to numerous complex human diseases,therefore,exploring miRNA-disease associations(MDAs)can help people gain a better understanding of complex disease *** increasing number of computational methods have been developed to predict ***,the sparsity of the MDAs may hinder the performance of many *** addition,many methods fail to capture the nonlinear relationships of miRNA-disease network and inadequately leverage the features of network and neighbor *** this study,we propose a deep matrix factorization model with variational autoencoder(DMFVAE)to predict potential *** first decomposes the original association matrix and the enhanced association matrix,in which the enhanced association matrix is enhanced by self-adjusting the nearest neighbor method,to obtain sparse vectors and dense vectors,***,the variational encoder is employed to obtain the nonlinear latent vectors of miRNA and disease for the sparse vectors,and meanwhile,node2vec is used to obtain the network structure embedding vectors of miRNA and disease for the dense ***,sample features are acquired by combining the latent vectors and network structure embedding vectors,and the final prediction is implemented by convolutional neural network with channel *** evaluate the performance of DMFVAE,we conduct five-fold cross validation on the HMDD v2.0 and HMDD v3.2 datasets and the results show that DMFVAE performs ***,case studies on lung neoplasms,colon neoplasms,and esophageal neoplasms confirm the ability of DMFVAE in identifying potential miRNAs for human diseases.

关键词： miRNA-disease association deep matrix factorization self-adjusted nearest neighbor variational encoder network structure

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Solving multi-object radar cross section based on wide-angle parabolic equation method

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Journal of Systems Engineering and Electronics 2006年第4期17卷 722-724页

作者： Huang Zhixiang Wu Qiong Wu Xianliang The Key Lab of Ministry of Education of Intelligent Computing & Signal Processing Anhui Univ. Hefei 230039 P. R. China

Based on a Pade approximation, a wide-angle parabolic equation method is introduced for computing the multiobject radar cross section （RCS） for the first time. The method is a paraxial version of the scalar wave equation, which solves the field by marching them along the paraxial direction. Numerical results show that a single wide-angle parabofic equation run can compute multi-object RCS efficiently for angles up to 45 ° . The method provides anew and efficient numerical method for computation electromagnetics.

关键词： parabolic equation method Pade approximation radar cross section paraxial direction.

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A BVP signal Detection Method of Anti-Motion Interference 12

A BVP Signal Detection Method of Anti-Motion Interference

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12th International Congress on Image and signal processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

作者： Wan, Qing Wu, Xiaopei Zhang, Chao Anhui University Intelligent Computing and Signal Processing Key Lab Hefei China

ISBN: (纸本)9781728148526

The noncontact detection methods of blood volume pulse (BVP) based on facial videos have become a hot spot in recent years. However, these kinds of methods are highly sensitive to face movement. To address this problem, a novel BVP detection method based on kanade-Iucas-tomasi (KLT) and independent component analysis (ICA) was proposed, in which, KLT method was employed for tracking and locating the region of interest (ROI) in facial images, and ICA method was used to improve the signal to noise ratio (SNR) of BVP signal. Based on 120 recorded facial videos, we carried out the comparative study of the proposed method and other commonly-used methods, the experimental results show that our method has obvious advantages in eliminating motion interference. In the implementation of the blind source separation method, we also conducted four separation methods. The results show that the second order blind identification (SOBI) algorithm is the best one to separate the BVP signal. © 2019 IEEE.

关键词： Blind source separation

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A NEW HIGH ACCURACY RETRIEVAL MODEL BASED ON QUOTIENT SPACE

A NEW HIGH ACCURACY RETRIEVAL MODEL BASED ON QUOTIENT SPACE

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2007中国宁波国际计算机科学与技术学术大会

作者： Yang Weimin Li Longshu Key Lab.of Intelligent Computing & Signal Processing Anhui University Ministry of Education Department of Computer Science and Engineering Anhui University

ISBN: (纸本)9780972147903

The effectiveness of ad-hoc retrieval systems appears to have reached a *** the research community is investigating an assortment of variables that will help them develop increasingly accurate retrieval *** paper presents a new method of high accuracy retrieval of document,which is based on quotient *** describes the problem space from different granularity:sentence,paragraph and document,and studies the relations among different granularities.

关键词： Quotient space High accuracy retrieval Granularity analysis Rough set

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