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2005 IEEE International Conference on Granular computing

作者： Chen, Wan L. Cheng, Jia X. Key Lab. of Intelligent Computing and Signal Processing Ministry of Education AnHui University HeiFei 230039 AnHui China

ISBN: (纸本)0780390172

Quotient space theory of problem solving, a formal model of granular computing, is generalized in the sense that topological structure is replaced by Cech's closure space. Some basic issues of granular computing, such as the representation of real world at different levels of granularity, property preserving and the construction of granular world, are discussed in detail. It turns out that most of conclusions of the classical quotient space theory keep being valid, so intension and applicable fields are enriched and enlarged respectively. © 2005 IEEE.

关键词： Problem solving

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A 5-Parameter bundld adjustment method for image mosaic

A 5-Parameter bundld adjustment method for image mosaic

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8th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2009

作者： Fang, Xianyong Luo, Bin Zhao, Haifeng Zhang, Yiwen Key Lab. of Intelligent Computing and Signal Processing of MOE School of Computer Science and Technology Anhui University China

ISBN: (纸本)9780769536415

A 5-parameter bundle adjustment method is proposed in this paper for global mosaic of an image sequence. By decomposing the rotation matrix into a 3-parameter rotation axis and a rotation angle, to each image, there are 5 parameters that need estimate for rotation axis, rotation angle and focal length. The proposed method minimizes the distance between feature matches in 3D space so that these 5 parameters are refined gradually for final stitching of all images together. Experimental results suggest that this method is an useful extension to existing research with the advantages of real 3D camera motion, accurate 5-parameter rotation decomposition and reliable 3D feature definition. © 2009 IEEE.

关键词： Rotation

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A new population diversity model in swarm intelligence

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Journal of Information and Computational Science 2009年第4期6卷 1891-1898页

作者： Feng, Jiqiang Xie, Weixin Xu, Chen Huang, Jianjun Key Lab. for Intelligent Information Processing Shenzhen University Shenzhen 518060 China Institute of Intelligent Computing Science Shenzhen University Shenzhen 518060 China

Many researchers of swarm intelligence (SI) algorithms take their ideas from physical and biological systems. This approach, however, is mostly qualitative and many ideas remain vague and ill-defined. In this paper, a mathematical framework based on probability theory is presented that enables us to analyze one important aspect of SI algorithms: the population diversity. Firstly the population density is defined for the population in the SI algorithms. The population diversity is then discussed from the point of view of the normal distribution in statistics. We show that there is a close connection between the distribution and population diversity and that the essential structure of population diversity is quite similar to that of the distribution. A detailed construction of the population diversity model is then given that is based on probability distributions and the convergence of the model is theoretically discussed for single peak value case. The paper concludes with a generic numerical example that validates the population diversity model. © 2009 Binary Information Press.

关键词： Normal distribution

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A graph and PNN-based approach to image classification

A graph and PNN-based approach to image classification

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International Conference on Machine Learning and Cybernetics, ICMLC 2005

作者： Tang, Jin Zhang, Chun-Yan Luo, Bin Key Lab of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China

ISBN: (纸本)078039092X

In this paper, a new image classification method is developed. This approach applies graph decomposition and probabilistic neural networks(PNN) to the task of supervised image classification. We use relational graphs to represent image. These graphs are constructed from the feature points of images. Spectra of these graphs will be obtained as feature vectors for classification. PNN is adopted to classifies image according to the feature vectors. Experimental results show that this method can achieve best result of images classification. ©2005 IEEE.

关键词： Image segmentation

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Localization Optimization Algorithm of Maximum Likelihood Estimation Based on Received signal Strength 9

Localization Optimization Algorithm of Maximum Likelihood Es...

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2017 9th IEEE International Conference on Communication Software and Networks (ICCSN 2017)

作者： Jun Zhu Qiang Chen Jingjing Zhang Key Lab of Intelligent Computing and Signal Processing Ministry of Education School of Electronics and Information Engineering Anhui University

ISBN: (纸本)9781509038237;9781509038220

In this paper, we propose a method to improve localization algorithm of maximum likelihood estimation;the localization scheme relies on the distance threshold. In order to suppress effectively the effects of received signal strength error to node localization precision. This paper presents an indoor localization algorithm based on received signal strength to select anchor nodes. Compared with the traditional localization algorithm, this scenario not only improve the localization accuracy, but also reduce the calculation complexity of nodes. The simulation results show that the average error of the proposed method is less than 0.15 m. Moreover, when there are a large number of anchor nodes, the computational complexity is effectively reduced. Verification result verifies the effectiveness and reliability of the algorithm.

关键词： localization received signal strength(RSS) maximum likelihood estimation(MLE) least squares threshold

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Speaker Recognition Based on the Improved Double-Threshold Endpoint Algorithm and Multistage Vector Quantization 9

Speaker Recognition Based on the Improved Double-Threshold E...

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2017 9th IEEE International Conference on Communication Software and Networks (ICCSN 2017)

作者： Jun Zhu Jingjing Zhang Qiang Chen Peipei Tu Key Lab of Intelligent Computing and Signal Processing Ministry of Education School of Electronics and Information Engineering Anhui University

ISBN: (纸本)9781509038237;9781509038220

The traditional double-threshold endpoint detection method has the phenomenon of missing detection. Therefore, the speech recognition(SR) system based on vector quantization(VQ) in this paper proposes an improved algorithm for this phenomenon, which effectively avoids the problem of missing detection. Then, Mel Frequency Cepstral Coefficients(MFCC) is used to extract the characteristic parameters of the speech signal, and the multistage vector quantization is used to quantify the characteristic parameters. Experimental results show that, the proposed algorithm improves the recognition rate of the text-independent speaker recognition system by 8.7%, and it also confirms that the longer the training speech is, the higher the recognition rate will be.

关键词： the multistage vector quantization MFCC double-threshold endpoint detection method missing detection characteristic parameters

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Study on moving target detection to passive radar based on FM broadcast transmitter

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Journal of Systems Engineering and Electronics 2007年第3期18卷 462-468页

作者： Zhu Jiabing Tao Liang Hong yi Education Ministry Key Lab of Intelligent Computing and Signal Processing Anhui Univ. Hefei 230039 P. R. China Inst. of Signal Processing East China Research Inst. of Electronic Engineering Hefei 230031 P. R. China

Target detection by a noncooperative illuminator is a topic of general interest in the electronic warfare field. First of all, direct-path interference （DPI） suppression which is the technique of bottleneck of moving target detection by a noncooperative frequency modulation（FM） broadcast transmitter is analyzed in this article; Secondly, a space-time-frequency domain synthetic solution to this problem is introduced： Adaptive nulling array processing is considered in the space domain, DPI cancellation based on adaptive fractional delay interpolation （AFDI） technique is used in planned time domain, and long-time coherent integration is utilized in the frequency domain; Finaily, an experimental system is planned by considering FM broadcast transmitter as a noncooperative illuminator, Simulation results by real collected data show that the proposed method has a better performance of moving target detection.

关键词： passive radar direct path interference adaptive beamforming adaptive fractional delay interpolation,long-time coherent integration.

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Linear Frequency Modulated signal Denoising Based on Symplectic Geometric Mode Decomposition and Block Thresholding 23

Linear Frequency Modulated Signal Denoising Based on Symplec...

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23rd IEEE International Conference on Communication Technology, ICCT 2023

作者： Ni, Jincheng Zhao, Jin Wu, Xianliang AnHui University Key Lab of Intelligent Computing & Signal Processing Ministry of Education Heifei China

ISBN: (纸本)9798350325959

In this paper, a novel and comprehensive signal denoising method is proposed by combining Symplectic Geometric Modal Decomposition (SGMD) and Block Thresholding denoising. The proposed approach involves a three-step process: first, the signal is decomposed into a set of Symplectic Geometric Components (SGCs) using SGMD. Subsequently, each SGC is subjected to Block-Thresholding denoising. Finally, the denoised SGCs are recombined to obtain the denoised linear frequency modulation (LFM) signal. The experimental verification demonstrates the effectiveness of the SGMD-BT method in denoising LFM signals. This novel approach offers a fresh solution for the processing and analysis of LFM signals, holding significant application potential and research importance. © 2023 IEEE.

关键词： Block Thresholding denoising signal denoising Symplectic Geometric Modal Decomposition

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Enhanced Symplectic Geometric Mode Decomposition via K-means Clustering for LFM signal Denoising 7

Enhanced Symplectic Geometric Mode Decomposition via K-means...

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7th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2024

作者： Ni, Jincheng Zhao, Jin Wu, Xianliang Wu, Ping AnHui University Key Lab of Intelligent Computing & Signal Processing Ministry of Education Hefei China

ISBN: (纸本)9798350384437

This article presents a Symplectic Geometric Mode Decomposition (SGMD) method incorporating K-means clustering, coupled with wavelet denoising, for mitigating noise in Linear Frequency Modulation (LFM) signals. This method substitutes the original component recombination approach in SGMD with the K-means clustering algorithm, thus rendering the signal grouping more logically coherent. In the experiment, we compare the method proposed in this article with other denoising methods. The experimental findings demonstrate substantial advantages of the proposed method in mitigating noise in LFM signals, thereby enhancing both signal-to-Noise Ratio (SNR) and signal quality. The research outcomes underscore the feasibility and substantial potential of this method in mitigating noise in signals. In subsequent studies, additional investigation into its applicability across diverse domains can be pursued alongside the refinement of clustering and denoising algorithms. © 2024 IEEE.

关键词： Wavelet decomposition

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Rate-embedded differential space-frequency codes based on cyclic delay diversity

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Journal of Computational Information Systems 2012年第1期8卷 151-158页

作者： Zhang, Hongwei Xu, Lei Li, Xiaohui Lu, Lu Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China Anhui Public Security Department Hefei 230061 China

The conventional differential space-frequency codes (DSFC) based on cyclic delay diversity (CDD) only could achieve the same transmission rate with that of a single transmit antenna system, the spectral efficiency was low. To improve the spectral efficiency in a non-coherent multiple antenna system, the advantage of CDD is considered fully in this paper and then a rate-embedded differential space-frequency coding scheme based on grouped CDD is proposed. In the proposed scheme, all transmit antennas are partitioned into several groups firstly, the conventional cyclic delays are adopted to achieve spatial diversity in each group, those symbols among different groups are transmitted differentially with low rate and high rate message matrices alternately, consequently high rate transmission is obtained. Simulation results verify that, compared with the conventional DSFC based on CDD, the proposed coding scheme can achieve obviously higher transmission rates and better error performances. © 2012 Binary Information Press January 2012.

关键词： Spectrum efficiency

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