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Design of multilayer cellular neural network based on memristor crossbar and its application to edge detection

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Journal of Systems engineering and Electronics 2023年第3期34卷 641-649页

作者： YU Yongbin TANG Haowen FENG Xiao WANG Xiangxiang HUANG Hang School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu 610054China

Memristor with memory properties can be applied to connection points(synapses)between cells in a cellular neural network(CNN).This paper highlights memristor crossbar-based multilayer CNN(MCM-CNN)and its application to edge detection.An MCM-CNN is designed by adopting a memristor crossbar composed of a pair of memristors.MCM-CNN based on the memristor crossbar with changeable weight is suitable for edge detection of a binary image and a color image considering its characteristics of programmablization and compactation.Figure of merit(FOM)is introduced to evaluate the proposed structure and several traditional edge detection operators for edge detection results.Experiment results show that the FOM of MCM-CNN is three times more than that of the traditional edge detection operators.

关键词： edge detection figure of merit(FOM) memristor crossbar synaptic circuit memristor crossbar-based cellular neural network(MCM-CNN)

Tuning-up Learning Parameters for Deep Convolutional Neural Network:A Case Study for Hand-Drawn Sketch Images

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Journal of Electronic Science and Technology 2022年第3期20卷 305-318页

作者： Shaukat Hayat Kun She Muhammad Mateen Parinya Suwansrikham Muhammad Abdullah Ahmed Alghaili the School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu 610054 the school of Big Data&software engineering Chongqing UniversityChongqing 400044 the College of information Science and engineering Hunan UniversityChangsha 410082

Several recent successes in deep learning(DL),such as state-of-the-art performance on several image classification benchmarks,have been achieved through the improved configuration.Hyperparameters(HPs)tuning is a key factor affecting the performance of machine learning(ML)algorithms.Various state-of-the-art DL models use different HPs in different ways for classification tasks on different datasets.This manuscript provides a brief overview of learning parameters and configuration techniques to show the benefits of using a large-scale handdrawn sketch dataset for classification problems.We analyzed the impact of different learning parameters and toplayer configurations with batch normalization(BN)and dropouts on the performance of the pre-trained visual geometry group 19(VGG-19).The analyzed learning parameters include different learning rates and momentum values of two different optimizers,such as stochastic gradient descent(SGD)and Adam.Our analysis demonstrates that using the SGD optimizer and learning parameters,such as small learning rates with high values of momentum,along with both BN and dropouts in top layers,has a good impact on the sketch image classification accuracy.

关键词： Deep learning(DL) hand-drawn sketches learning parameters

Crowd queuing simulation with an improved emotional contagion model

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Science China(information Sciences) 2019年第4期62卷 197-199页

作者： Junxiao XUE Hui YIN Pei LV Mingliang XU Yafei LI school of software Zhengzhou University school of information engineering Zhengzhou University

In crowd queuing events, the emotions of individuals are mutually infective, easily confusing the queuing order and possibly leading to crowd events. However, the impact of emotion and personality is not considered in... 详细信息

关键词： Crowd queuing simulation with an improved emotional contagion model

Multi-Hop Transmission Method of 5G Millimeter Wave Relay Based on Network Coding

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China Communications 2022年第12期19卷 14-26页

作者： Yilin Wang Weisheng He Xuwei Fan Lianfen Huang Jie Yang Yuliang Tang school of information Xiamen UniversityXiamen 361005China Department of software engineering Xiamen Institute of Software TechnologyXiamen 361005China

With the rapid development of the Internet technology,millimeter wave(mmWave)will be used as a supplement to 5G low frequency bands to meet the extremely high system capacity requirements of 5G in hot spots.Although 5G mmWave communication can adapt to the needs of 5G network and carry a large amount of transmitted data,transmission stability has become one of the key technical issues of 5G network mmWave communication due to problems such as strong attenuation and poor penetration of mmWave.In order to improve the efficiency of the mmWave multi-hop transmission,we propose a 5G mmWave multi-hop transmission method based on network coding,which can adapt to the current wireless network environment,improve spectrum efficiency and increase network throughput.Based on MATLAB simulation experiments,it is verified that the proposed method can greatly improve the transmission efficiency and reduce the signal loss under the premise of ensuring the accurate signal transmission.

关键词： 5G network millimeter wave relay multihop communication network coding

A Robust Fuzzy Time Series Forecasting Method Based on Multi-partition and Outlier Detection

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Chinese Journal of Electronics 2019年第5期28卷 899-905页

作者： QU Hua ZHANG Yanpeng LIU Wei ZHAO Jihong school of software engineering Xi'an Jiaotong University school of Electronics and information engineering Xi'an Jiaotong University school of Communication and information engineering Xi'an University of Posts and Telecommunication

We propose a robust fuzzy time series forecasting method based on multi-partition approach and outlier detection for forecasting market prices. The multipartition approach employs a specific partition criterion for each dimension of the time series. We use a Gaussian kernel version fuzzy C-means clustering to construct the fuzzy logic relationships and detect the outliers by calculating the grade of membership. We apply an additional model, which is trained on the set of outliers by Levenberg-Marquardt algorithm, for forecasting the outliers in testing set. The experiment results show that the proposed method improves the robustness and the average forecasting accuracy rate.

关键词： Fuzzy time series Multi-partition approach Outlier detection

Automatic Construction of Floor Plan with Smartphone Sensors

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Journal of Electronic Science and Technology 2019年第1期17卷 13-25页

作者： Rui Zhou Xiang Lu Hao-Sen Zhao Yang Fu Ming-Jie Tang the School of Information and Software Engineering University of Electronic Science and Technology of China

Indoor floor plans are of vital importance for a wide range of indoor social applications, however, they are often unavailable due to various reasons. This paper proposes a method to automatically construct the indoor floor plan with rooms and corridors as well as landmarks, using inertial traces collected with smartphones. Landmarks,such as turnings, doors, and stairs, are identified according to inertial sensors and WiFi signals. The inertial traces are then partitioned into segments according to the turnings and classified as room type or corridor type according to the doors. Clustering is applied on room type and corridor type trace segments separately to produce room type and corridor type clusters. The construction of room applies the α-shape algorithm on room type clusters and the construction of corridor employs the principal component analysis(PCA) algorithm or the α-shape algorithm on corridor type clusters. Evaluations in two representative scenarios show that the method can construct the floor plan of acceptable accuracy with a relatively small set of inertial traces.

关键词： Clustering floor plan construction pedestrian dead reckoning smartphone sensor

Resource Allocation for Device-to-Device Communications Based on Guard Area Underlying Cellular Networks

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Chinese Journal of Electronics 2017年第6期26卷 1297-1301页

作者： WANG Gang XIONG Liufei YUAN Cangzhou school of Electrical and information engineering Beihang University school of software Beihang University

Device-to-Device(D2D) communications have drawn considerable attention with the obvious advantages of a higher data rate and spectrum efficiency. However, this also brings intra-cell interference due to resource sharing with traditional Cellular users(CUs). An effective resource allocation scheme for D2D communications to maximize the system throughput is developed. This scheme first utilizes the guard area model to restrict the interference between D2D users(DUs) and CUs. Then, a max-flow algorithm is used to match the pair of CUs and DUs and maximize the total sum rate of the communication system. Numeral results demonstrate that the proposed scheme can yield significant throughput gain while maintaining quality for both CUs and DUs.

关键词： Device-to-device(D2D) communications Guard area Power allocation

A Method for Bio-Sequence Analysis Algorithm Development Based on the PAR Platform

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Big Data Mining and Analytics 2023年第1期6卷 11-20页

作者： Haipeng Shi Huan Chen Qinghong Yang Jun Wang Haihe Shi school of software Jiangxi Normal UniversityNanchang 330022China school of Computer and information engineering Jiangxi Normal UniversityNanchang 330022China

The problems of biological sequence analysis have great theoretical and practical value in modern bioinformatics.Numerous solving algorithms are used for these problems,and complex similarities and differences exist among these algorithms for the same problem,causing difficulty for researchers to select the appropriate one.To address this situation,combined with the formal partition-and-recur method,component technology,domain engineering,and generic programming,the paper presents a method for the development of a family of biological sequence analysis algorithms.It designs highly trustworthy reusable domain algorithm components and further assembles them to generate specifific biological sequence analysis algorithms.The experiment of the development of a dynamic programming based LCS algorithm family shows the proposed method enables the improvement of the reliability,understandability,and development efficiency of particular algorithms.

关键词： partition-and-recur(PAR) domain engineering biological sequences feature model component assembly

Query Acceleration of Graph Databases by ID Caching Technology

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Journal of Electronic Science and Technology 2019年第1期17卷 41-50页

作者： Wei Jiang Hai-Bo Hu Liu-Gen Xu the School of Information and Software Engineering University of Electronic Science and Technology of China

In this paper, we approach the design of ID caching technology(IDCT) for graph databases, with the purpose of accelerating the queries on graph database data and avoiding redundant graph database query operations which will consume great computer resources. Traditional graph database caching technology(GDCT)needs a large memory to store data and has the problems of serious data consistency and low cache utilization. To address these issues, in the paper we propose a new technology which focuses on ID allocation mechanism and high-speed queries of ID on graph databases. Specifically, ID of the query result is cached in memory and data consistency is achieved through the real-time synchronization and cache memory adaptation. In addition, we set up complex queries and simple queries to satisfy all query requirements and design a mechanism of cache replacement based on query action time, query times, and memory capacity, thus improving the performance furthermore.Extensive experiments show the superiority of our techniques compared with the traditional query approach of graph databases.

关键词： Cache graph database query efficiency