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检索条件"机构=Tianjin Intelligent Computing and Software New Technology Key Laboratory"

共 168 条记录，以下是61-70 订阅

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Spike sorting based on radial basis function network with overlap decomposition

Spike sorting based on radial basis function network with ov...

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作者： Dai, Min Hu, Su-Rui Qi, Jia Tianjin Key Lab of Intelligent Computing and Novel Software Technology School of Computer and Communication Engineering Tianjin University of Technology Tianjin 300191 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin 300191 China

Spike sorting is the essential step in analyzing recording spike signals for studying information processing mechanisms within the nervous system. Overlapping is one of the most serious problems in the spike sorting for multi-channel recordings. In this paper, a modified radial basis function (RBF) network is proposed to decompose the overlapping signals and separate spikes within the same RBF network. A modified radial basis function based on the Gaussian function is employed in the method to improve the accuracy of overlap decomposition. In addition, the improved constructing algorithm reduces the calculation cost by taking advantage of the symmetry of the RBF network. The performance of the presented method is tested at various signal-to-noise ratio levels based on simulated data coming from the University of Leicester and Wave-clus software. Experiment results show that our method successfully solves the fully overlapping problem and has higher accuracy comparing with the Gaussian function. © 2011 Elsevier Ltd. All rights reserved.

关键词： Radial basis function networks

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A clustering algorithm use SOM and K-Means in Intrusion Detection

A clustering algorithm use SOM and K-Means in Intrusion Dete...

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International Conference on E-Business and E-Government (ICEE)

作者： Wang, Huai-Bin Yang, Hong-Liang Xu, Zhi-Jian Yuan, Zheng Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin University of Technology 300191 Tianjin China Key Laboratory of Computer Vision and System Ministry of Education 300191 Tianjin China Key Laboratory of Computer Vision and System Ministry of Education China

ISBN: (纸本)9780769539973

Improving detection definition is a pivotal problem for intrusion detection. Many intelligent algorithms were used to improve the detection rate and reduce the false rate. Traditional SOM cannot provide the precise clustering results to us, while traditional K-Means depends on the initial value serious and it is difficult to find the center of cluster easily. Therefore, in this paper we introduce a new algorithm, first, we use SOM gained roughly clusters and center of clusters, then, using K-Means refine the clustering in the SOM stage. At last of this paper we take KDD CUP-99 dataset to test the performance of the new algorithm. The new algorithm overcomes the defects of traditional algorithms effectively. Experimental results show that the new algorithm has a good stability of efficiency and clustering accuracy. © 2010 IEEE.

关键词： Self organizing maps

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DNS Covert Channel Attack Detection Based on Spatio-Temporal Feature Fusion 22

DNS Covert Channel Attack Detection Based on Spatio-Temporal...

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22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： You, Wei Zhao, Chunlei Shan, Chao Dong, Guozhong Yu, Jie Guan, Yong Tianjin University of Technology Tianjin Key Laboratory of Intelligent Computing and Software New Technology Tianjin China Coordination Center of China Hubei Branch of National Computer Network Emergency Response Technical Team HuBei China Pengcheng Laboratory Department of New Networks Shenzhen China

ISBN: (纸本)9798331509712

An increasing number of Advanced Persistent Threat (APT) organizations are utilizing DNS (Domain Name System) covert channels to evade network intrusion detection systems and establish private authoritative servers for remote attacks. However, current detection models for DNS covert channels often have poor performance and limited generalization ability. To address these challenges, we propose a DNS covert channel attack detection method based on spatiotemporal feature fusion. This method combines the Interaction timing sequence features of DNS traffic with the spatial statistical features of domain names, and constructs a detection model called ConvSLSTM, which integrates a Convolutional Neural Network (CNN) with a stacked Long Short Term Memory (LSTM) network. CNN extracts local spatial features from traffic, while stacked LSTM captures Interaction timing sequence features, significantly improving detection accuracy. This article uses three typical public datasets for experiments, which contain a total of 440000 DNS covert channel attack data. Comparative experiments show that our method is significantly superior to existing methods and exhibits stronger generalization ability in detecting DNS covert channel attacks constructed by unknown tools. © 2024 IEEE.

关键词： Network intrusion

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Dynamic Random Route Mutation Mechanism for Moving Target Defense in SDN 6

Dynamic Random Route Mutation Mechanism for Moving Target De...

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6th International Symposium on Computer and Information Processing technology, ISCIPT 2021

作者： Zhang, Bofeng Han, Li Sun, Shimin Tianjin University of Technology School of Computer Science and Engineering Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology National Engineering Laboratory for Computer Virus Prevention and Control Technology Tianjin China Tiangong University Tianjin Key Laboratory of Autonomous Intelligent Technology and System School of Computer Science and Technology Tianjin China

ISBN: (纸本)9781665441377

Moving Target Defense (MTD) is commonly used in changing the asymmetric situation between attack and defense in cyberspace. Route mutation is a vital branch of MTD. Current route mutation methods still have some limitations on unpredictability of mutating routing paths and time overhead. In this paper, we propose a Dynamic Random Route Mutation (DRRM) mechanism in order to maximize the unpredictability of mutation and reduce the time overhead. First, we adopt Jaccard distance matrix and temporal constraint to improve mutation space. Mutation space can be dynamically shifted to enhance the unpredictability. Then, we weaken attackers' capabilities of launching effective eavesdropping at a certain node by using route weight. Finally, we construct a pre-distribution strategy to reduce the transmission latency caused by route mutation. Simulation results show that DRRM not only raises the difficulty of network eavesdropping, but also ensures low mutation time overhead. © 2021 IEEE.

关键词： Dynamics

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A pervasive service discovery strategy based on peer to peer model

A pervasive service discovery strategy based on peer to peer...

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作者： Zhang, De-Gan Chen, Xu-Yan Li, Chao Li, Lin-Qing Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology 300191 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology 300191 China

ISBN: (纸本)9780955529337

In order to improve the efficiency of service discovery in the pervasive environment, this paper presents a new strategy of service discovery based on p2p network model. Reference the ring topology of chord algorithm and tbe algorithm used by DDT, tbe traditional single finger-table witch be maintained by each node in the ring will be changed into double finger-table: the Neigbbor-Finger-Table and Long-distance Finger-Table. The structure of the Neighbor-Finger-Table is the same as the traditional single finger-table's. The Long-distance Finger-Table can construct small-world network. Some similar algorithm uses random method to select remote access node, the new strategy is different from that, tbrough tbe calculation of the local node, it can ensure the scope of service can cover tbe entire network. The simulation shows the algorithm can effectively reduce the path length of service discovery, improve the service success rate, and control the path length of magnitude.

关键词： Small-world networks

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A new method for image fusion based on fuzzy neural network

A new method for image fusion based on fuzzy neural network

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作者： Zhang, De-Gan Wang, Yuan-Yuan Liu, Wei-Wei Zhang, Xiao-Li Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology 300191 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology 300191 China

ISBN: (纸本)9780955529337

In pervasive computing paradigm, the image data obtained by a variety of multimedia, information equipment. In order to make use of these information reasonably and efficiently, a new method for image fusion based on fuzzy neural network has presented in this paper. It can fuse massive data from the multi-sensor image. Here, fuzzy neural network is a paraDel information processing model, there are more adaptive and self-organization, and can accomplish the complexity of real-time computing and mass data retrieval, it demonstrate its unique superiority of image understanding, pattern recognition and the handling of incomplete information. The fuzzy neural network system developed by us can be used in multi- sensor image fusion. Based on our experiments, it has been proved that the fusion is fast, effective, and can meet the real-time requirements of pervasive computing.

关键词： Fuzzy neural networks

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Node Coupling for Inferring Networks from Short Time Series 5th

Node Coupling for Inferring Networks from Short Time Series

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5th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2021

作者： Li, Hang Wang, Li Xia, Chengyi Tianjin University of Technology Tianjin300382 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China Engineering Research Center of Learning-Based Intelligent System Ministry of Education Beijing China

ISBN: (纸本)9789811939976

Commonly abstracted as a set of units, the complex systems in the real world are interconnected with each other using the specific dynamical methods. However, in practice, there is nothing else but the performances of the system known, nor are the network structure and the dynamical rules observed. In order to solve this problem, a research has been conducted on network reconstruction, so as to recover the potential network structure and network dynamics from the observed time series. In this paper, a new method is proposed, namely, slope difference similarity (SDS), which is a way of thinking in reverse. Based on the trend of change in nodes, the coupling degree between nodes is judged and the network is reconstructed. By comparing the SDS and Kendall rank correlation method with experiments, the experimental results are obtained in this paper to demonstrate the effectiveness of SDS network reconstruction. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Time series

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A Kind of new parallax algorithm based on symmetric continuous optimization 5

A Kind of new parallax algorithm based on symmetric continuo...

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2020 5th International Seminar on Computer technology, Mechanical and Electrical Engineering, ISCME 2020

作者： Jiang, Kaiwen Zhang, Degan Xu, Haixia Key Laboratory of Computer Vision and System Tianjin University of Technology Ministry of Education 300384 China Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin China School of Electronic and Information Engineering Tianjin Vocational Institute Tianjin300410 China

With the fast development of 3D imaginations becomes more and more fascination, multi-view stereo based 3D reconstruction is a significant technique for those application. To facilitate the subsequent processing of 3D reconstruction and reduce the possibility of other algorithms falling into local optimal solutions, attempting to get better and faster performance, a new parallax calculation based on symmetric continuous optimization is proposed in this paper. The algorithm is proposed here will be tested respectively in the same data, in order to certificate the algorithm applied is better than traditional minimize El algorithm. © Published under licence by IOP Publishing Ltd.

关键词： Optimization

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Semi-supervised classification method of SAR images using spectral clustering in contourlet domain 4

Semi-supervised classification method of SAR images using sp...

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2019 4th International Seminar on Computer technology, Mechanical and Electrical Engineering, ISCME 2019

A new based on Semi-supervised classification theory for SAR images in contourlet domain is proposed, in this paper. Attempting to get better and faster performance, the PSO algorithm (Particle swarm optimization algorithm) and contourlet domain is proposed to instead of traditional k-means algorithm. PSO is used to find the global optimum by performing a global search in the whole solution space. And then, contourlet is applied in front of construct the similarity matrix to extract more effective eigenvalues. In section five, the proposed algorithm got better classification results than the traditional k-means algorithm which is proved by experimental results show that in terms of running time, classification accuracy and Kappa coefficient. © Published under licence by IOP Publishing Ltd.

关键词： Synthetic aperture radar

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Ecg Based Identification Under Different Physical Status

Ecg Based Identification Under Different Physical Status

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Gang Zheng Hong-Yuan Zhang Shen-Zhen Ji Tianjin Key Laboratory of Intelligent Computing and Software New Technique Tianjin University of Technology Tianjin China

ISBN: (纸本)9781538652152

Relatively stable feature of Electrocardiogram (ECG) waveform in ECG based identification authentication is an important issue to be discovered in biometric. It can benefit the biomaterial which is weak and easy to be affected when it is collected under different physical status. From the paper, it was found that P waveform was stable when several ECG waveforms were overlapped under Matthew Effect rule, therefore P waveform period could be more dependent than other part of ECG waveform in identity. And this result was used in the following experiments. The experiments in the paper were designed to study whether ECG based identification was affected by the status of ECG signal collecting. The status contained four status pairs, that was, emotion status (calm, high pressure), eating (starve, satition), sleeping (full, lack) and health (healthy, tired/cold). From the result, Negative emotion and lacking sleeping reduced TPR slightly (about 2-3%), but there was no effect on both eating and health pair status. However, if we used ECG data mixed with all four statuses, the overall True Positive Rate (TPR) of identification reached around 85%.

关键词： Electrocardiography Authentication Training Heart beat Feature extraction Shape Frequency-domain analysis

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