• Title/Summary/Keyword: SVD(Singular Value Decomposition)

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A Study on System Identification of Active Magnetic Bearing Rotor System Considering Sensor and Actuator Dynamics (센서와 작동기를 고려한 자기베어링 시스템의 식별에 관한 연구)

  • Kim, Chan-Jung;Ahn, Hyeong-Joon;Han, Dong-Chul
    • Proceedings of the KSME Conference
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    • 2003.11a
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    • pp.1458-1463
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    • 2003
  • This paper presents an improved identification algorithm of active magnetic bearing rotor systems considering sensor and actuator dynamics. An AMB rotor system has both real and complex poles so that it is very hard to identify them together. In previous research, a linear transformation through a fictitious proportional feedback was used in order to shift the real poles close to the imaginary axis. However, the identification result highly depends on the fictitious feedback gain, and it is not easy to identify the additional dynamics including sensor and actuators at the same time. First, this paper discusses the necessity and a selection criterion of the fictitious feedback gain. An appropriate feedback gain minimizes dominant SVD(Singular Value Decomposition) error through maximizing rank deficiency. Second, more improvement in the identification is achieved through separating the common additional dynamics in all elements of frequency response matrix. The feasibility of the proposed identification algorithm is proved with two theoretical AMB rotor models. Finally, the proposed scheme is compared with previous identification methods using experimental data, and a great improvement in model quality and large amount of time saving can be achieved with the proposed method.

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SVD-LDA: A Combined Model for Text Classification

  • Hai, Nguyen Cao Truong;Kim, Kyung-Im;Park, Hyuk-Ro
    • Journal of Information Processing Systems
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    • v.5 no.1
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    • pp.5-10
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    • 2009
  • Text data has always accounted for a major portion of the world's information. As the volume of information increases exponentially, the portion of text data also increases significantly. Text classification is therefore still an important area of research. LDA is an updated, probabilistic model which has been used in many applications in many other fields. As regards text data, LDA also has many applications, which has been applied various enhancements. However, it seems that no applications take care of the input for LDA. In this paper, we suggest a way to map the input space to a reduced space, which may avoid the unreliability, ambiguity and redundancy of individual terms as descriptors. The purpose of this paper is to show that LDA can be perfectly performed in a "clean and clear" space. Experiments are conducted on 20 News Groups data sets. The results show that the proposed method can boost the classification results when the appropriate choice of rank of the reduced space is determined.

Joint Lattice-Reduction-Aided Precoder Design for Multiuser MIMO Relay System

  • Jiang, Hua;Cheng, Hao;Shen, Lizhen;Liu, Guoqing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.7
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    • pp.3010-3025
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    • 2016
  • Lattice reduction (LR) has been used widely in conventional multiple-input multiple-output (MIMO) systems to enhance the performance. However, LR is hard to be applied to the relay systems which are important but more complicated in the wireless communication theory. This paper introduces a new viewpoint for utilizing LR in multiuser MIMO relay systems. The vector precoding (VP) is designed along with zero force (ZF) criterion and minimum mean square error (MMSE) criterion and enhanced by LR algorithm. This implementable precoder design combines nonlinear processing at the base station (BS) and linear processing at the relay. This precoder is capable of avoiding multiuser interference (MUI) at the mobile stations (MSs) and achieving excellent performance. Moreover, it is shown that the amount of feedback information is much less than that of the singular value decomposition (SVD) design. Simulation results show that the proposed scheme using the complex version of the Lenstra--Lenstra--Lovász (LLL) algorithm significantly improves system performance.

Performance Analysis of Precoded LTE-Advanced Uplink System (LTE-Advanced 시스템의 선부호화된 상향 링크 성능 분석)

  • Kim, Sang-Gu;Li, Xun;Kim, Young-Ju
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.48 no.5
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    • pp.8-15
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    • 2011
  • LTE-Advanced aims at peak data rates of 1Gbits/s for the downlink and 500 Mbits/s for the uplink, which can be accomplished only by using wide spectrum allocation of 100MHz as well as advanced multiple input multiple output antenna techniques to the uplink. This paper analyzes the uplink precoding techniques which include LTE codebook of downlink, singular value decomposition codebook, and equal gain transmission codebook over LTE defined single carrier frequency division multiplexing systems. Finally considering nonlinear transmit power amplifier model, it is shown that link-level performance of EGT is superior to those of any other precoding schemes.

Numerical Experiments of Ocean Acoustic Tomography in the East Sea of Korea

  • Han, Sang-Kyu;Na, Jung-Yul;Lee, Jae-Hak
    • Journal of the korean society of oceanography
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    • v.31 no.2
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    • pp.64-74
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    • 1996
  • Numerical experiments of OAT (Ocean Acoustic Tomography) are carried out in the East Sea of Korea where the canonical ocean has been perturbed by a mesoscale warm eddy and a thermal front. In order to estimate the horizontal and vertical structure of water temperature of the perturbed ocean, the experimental area is divided into 16 cells with 8 pairs of sources and receivers for a horizontal slice and the water column is divided into 8 layers for a vertical slice. The inversely estimated temperature field by using SVD (Singular Value Decomposition) method reveals the eddy and frontal structure clearly. The rms errors of the two horizontal slices are less than $0.4^{\circ}C$ and $1.7^{\circ}C$ at 400 m and 200 m depths, respectively, while the error in the vertical slice is less than $1.0^{\circ}C.$ For better estimation of temperature by OAT method, particularly for the East Sea, a range-dependent ray model should be used to solve the forward problem. At the same time, improvement in computing the refracted ray path between vertical layers is required to obtain more accurate travel time information. The results of the present experiment give rise to a possibility of application of OAT in remote sensing of the ocean thermal structure.

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SAR Image De-noising Based on Residual Image Fusion and Sparse Representation

  • Ma, Xiaole;Hu, Shaohai;Yang, Dongsheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.7
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    • pp.3620-3637
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    • 2019
  • Since the birth of Synthetic Aperture Radar (SAR), it has been widely used in the military field and so on. However, the existence of speckle noise makes a good deal inconvenience for the subsequent image processing. The continuous development of sparse representation (SR) opens a new field for the speckle suppressing of SAR image. Although the SR de-noising may be effective, the over-smooth phenomenon still has bad influence on the integrity of the image information. In this paper, one novel SAR image de-noising method based on residual image fusion and sparse representation is proposed. Firstly we can get the similar block groups by the non-local similar block matching method (NLS-BM). Then SR de-noising based on the adaptive K-means singular value decomposition (K-SVD) is adopted to obtain the initial de-noised image and residual image. The residual image is processed by Shearlet transform (ST), and the corresponding de-noising methods are applied on it. Finally, in ST domain the low-frequency and high-frequency components of the initial de-noised and residual image are fused respectively by relevant fusion rules. The final de-noised image can be recovered by inverse ST. Experimental results show the proposed method can not only suppress the speckle effectively, but also save more details and other useful information of the original SAR image, which could provide more authentic and credible records for the follow-up image processing.

Zero-Watermarking Algorithm in Transform Domain Based on RGB Channel and Voting Strategy

  • Zheng, Qiumei;Liu, Nan;Cao, Baoqin;Wang, Fenghua;Yang, Yanan
    • Journal of Information Processing Systems
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    • v.16 no.6
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    • pp.1391-1406
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    • 2020
  • A zero-watermarking algorithm in transform domain based on RGB channel and voting strategy is proposed. The registration and identification of ownership have achieved copyright protection for color images. In the ownership registration, discrete wavelet transform (DWT), discrete cosine transform (DCT), and singular value decomposition (SVD) are used comprehensively because they have the characteristics of multi-resolution, energy concentration and stability, which is conducive to improving the robustness of the proposed algorithm. In order to take full advantage of the characteristics of the image, we use three channels of R, G, and B of a color image to construct three master shares, instead of using data from only one channel. Then, in order to improve security, the master share is superimposed with the copyright watermark encrypted by the owner's key to generate an ownership share. When the ownership is authenticated, copyright watermarks are extracted from the three channels of the disputed image. Then using voting decisions, the final copyright information is determined by comparing the extracted three watermarks bit by bit. Experimental results show that the proposed zero watermarking scheme is robust to conventional attacks such as JPEG compression, noise addition, filtering and tampering, and has higher stability in various common color images.

Low Complexity Hybrid Precoding in Millimeter Wave Massive MIMO Systems

  • Cheng, Tongtong;He, Yigang;Wu, Yuting;Ning, Shuguang;Sui, Yongbo;Huang, Yuan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.4
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    • pp.1330-1350
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    • 2022
  • As a preprocessing operation of transmitter antennas, the hybrid precoding is restricted by the limited computing resources of the transmitter. Therefore, this paper proposes a novel hybrid precoding that guarantees the communication efficiency with low complexity and a fast computational speed. First, the analog and digital precoding matrix is derived from the maximum eigenvectors of the channel matrix in the sub-connected architecture to maximize the communication rate. Second, the extended power iteration (EPI) is utilized to obtain the maximum eigenvalues and their eigenvectors of the channel matrix, which reduces the computational complexity caused by the singular value decomposition (SVD). Third, the Aitken acceleration method is utilized to further improve the convergence rate of the EPI algorithm. Finally, the hybrid precoding based on the EPI method and the Aitken acceleration algorithm is evaluated in millimeter-wave (mmWave) massive multiple-input and multiple-output (MIMO) systems. The experimental results show that the proposed method can reduce the computational complexity with the high performance in mmWave massive MIMO systems. The method has the wide application prospect in future wireless communication systems.

Content-based image retrieval using a fusion of global and local features

  • Hee Hyung Bu;Nam Chul Kim;Sung Ho Kim
    • ETRI Journal
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    • v.45 no.3
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    • pp.505-517
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    • 2023
  • Color, texture, and shape act as important information for images in human recognition. For content-based image retrieval, many studies have combined color, texture, and shape features to improve the retrieval performance. However, there have not been many powerful methods for combining all color, texture, and shape features. This study proposes a content-based image retrieval method that uses the combined local and global features of color, texture, and shape. The color features are extracted from the color autocorrelogram; the texture features are extracted from the magnitude of a complete local binary pattern and the Gabor local correlation revealing local image characteristics; and the shape features are extracted from singular value decomposition that reflects global image characteristics. In this work, an experiment is performed to compare the proposed method with those that use our partial features and some existing techniques. The results show an average precision that is 19.60% higher than those of existing methods and 9.09% higher than those of recent ones. In conclusion, our proposed method is superior over other methods in terms of retrieval performance.

A New Robust Blind Crypto-Watermarking Method for Medical Images Security

  • Mohamed Boussif;Oussema Boufares;Aloui Noureddine;Adnene Cherif
    • International Journal of Computer Science & Network Security
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    • v.24 no.3
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    • pp.93-100
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    • 2024
  • In this paper, we propose a novel robust blind crypto-watermarking method for medical images security based on hiding of DICOM patient information (patient name, age...) in the medical imaging. The DICOM patient information is encrypted using the AES standard algorithm before its insertion in the medical image. The cover image is divided in blocks of 8x8, in each we insert 1-bit of the encrypted watermark in the hybrid transform domain by applying respectively the 2D-LWT (Lifting wavelet transforms), the 2D-DCT (discrete cosine transforms), and the SVD (singular value decomposition). The scheme is tested by applying various attacks such as noise, filtering and compression. Experimental results show that no visible difference between the watermarked images and the original images and the test against attack shows the good robustness of the proposed algorithm.