• Title/Summary/Keyword: linear filtering

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A Hybrid Collaborative Filtering Using a Low-dimensional Linear Model (저차원 선형 모델을 이용한 하이브리드 협력적 여과)

  • Ko, Su-Jeong
    • Journal of KIISE:Software and Applications
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    • v.36 no.10
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    • pp.777-785
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    • 2009
  • Collaborative filtering is a technique used to predict whether a particular user will like a particular item. User-based or item-based collaborative techniques have been used extensively in many commercial recommender systems. In this paper, a hybrid collaborative filtering method that combines user-based and item-based methods using a low-dimensional linear model is proposed. The proposed method solves the problems of sparsity and a large database by using NMF among the low-dimensional linear models. In collaborative filtering systems the methods using the NMF are useful in expressing users as semantic relations. However, they are model-based methods and the process of computation is complex, so they can not recommend items dynamically. In order to complement the shortcomings, the proposed method clusters users into groups by using NMF and selects features of groups by using TF-IDF. Mutual information is then used to compute similarities between items. The proposed method clusters users into groups and extracts features of groups on offline and determines the most suitable group for an active user using the features of groups on online. Finally, the proposed method reduces the time required to classify an active user into a group and outperforms previous methods by combining user-based and item-based collaborative filtering methods.

Evaluation of MR-SENSE Reconstruction by Filtering Effect and Spatial Resolution of the Sensitivity Map for the Simulation-Based Linear Coil Array (선형적 위상배열 코일구조의 시뮬레이션을 통한 민감도지도의 공간 해상도 및 필터링 변화에 따른 MR-SENSE 영상재구성 평가)

  • Lee, D.H.;Hong, C.P.;Han, B.S.;Kim, H.J.;Suh, J.J.;Kim, S.H.;Lee, C.H.;Lee, M.W.
    • Journal of Biomedical Engineering Research
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    • v.32 no.3
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    • pp.245-250
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    • 2011
  • Parallel imaging technique can provide several advantages for a multitude of MRI applications. Especially, in SENSE technique, sensitivity maps were always required in order to determine the reconstruction matrix, therefore, a number of difference approaches using sensitivity information from coils have been demonstrated to improve of image quality. Moreover, many filtering methods were proposed such as adaptive matched filter and nonlinear diffusion technique to optimize the suppression of background noise and to improve of image quality. In this study, we performed SENSE reconstruction using computer simulations to confirm the most suitable method for the feasibility of filtering effect and according to changing order of polynomial fit that were applied on variation of spatial resolution of sensitivity map. The image was obtained at 0.32T(Magfinder II, Genpia, Korea) MRI system using spin-echo pulse sequence(TR/TE = 500/20 ms, FOV = 300 mm, matrix = $128{\times}128$, thickness = 8 mm). For the simulation, obtained image was multiplied with four linear-array coil sensitivities which were formed of 2D-gaussian distribution and the image was complex white gaussian noise was added. Image processing was separated to apply two methods which were polynomial fitting and filtering according to spatial resolution of sensitivity map and each coil image was subsampled corresponding to reduction factor(r-factor) of 2 and 4. The results were compared to mean value of geomety factor(g-factor) and artifact power(AP) according to r-factor 2 and 4. Our results were represented while changing of spatial resolution of sensitivity map and r-factor, polynomial fit methods were represented the better results compared with general filtering methods. Although our result had limitation of computer simulation study instead of applying to experiment and coil geometric array such as linear, our method may be useful for determination of optimal sensitivity map in a linear coil array.

Reverse Filtering of Sound Field by Adaptive Filter and Neural Network (적응필터 및 신경회로망에 의한 음장의 역 필터링)

  • Choi, Jae-Seung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.5 no.2
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    • pp.145-151
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    • 2010
  • This paper proposes a reverse filtering system of sound field obtaining a state of sound field transmitted from two sounds, using an adaptive filter and neural network. The proposed system uses the reverse filtering method with calculating and renewing a coefficient of a filter, using least mean square. Based on training the neural network, experiments confirm that the proposed system is effective for a simple waveform with non-linear distortion, by using neural network and adaptive filtering method.

Development of Continuous/Discrete Mixed $H_2$/H$\infty$ Filtering Design Algorithms for Time Delay Systems

  • Kim, Jong-Hae
    • Transactions on Control, Automation and Systems Engineering
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    • v.2 no.3
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    • pp.163-168
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    • 2000
  • The problems of mixed $H_2/H_{\infty}$ filtering design fer continuous and discrete time linear systems with time delay are investigated. The main purpose is to design a stable mixed $H_2/H_{\infty}$ filter which minimizes the H$_2$Performance measure satisfying a prescribed H$_{\infty}$ norm bound on the closed loop system in continuous-time case and discrete-time case, respectively. The sufficient conditions of existence of filter, the mixed $H_2/H_{\infty}$ filter design method, and the upper bound of performance measure are proposed by LMI(linear matrix inequality) techniques in terms of all finding variables. Also, we present optimization problems in order to get the optimal mixed $H_2/H_{\infty}$ filter in continuous and discrete time case, respectively.

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Fault Diagnosis for Cable Using Reflectometry Based on Linear Kalman Filtering (케이블 고장 진단을 위한 선형 칼만필터 기반 반사파 계측법 연구)

  • Lee, Chun-Ku;Yoon, Tae-Sung;Park, Jin-Bae
    • Proceedings of the IEEK Conference
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    • 2009.05a
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    • pp.19-21
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    • 2009
  • The reflectometry for locating the fault at a cable is the same as a problem estimating the time delay between the incident and the reflected signals. In this paper, we propose a method for estimating the time delay between the two signals. The proposed method is based on the modeling of the Gaussian enveloped linear chirp signal in the Gaussian noise environment. The phase and the instantaneous frequency of the received signal are estimated by linear Kalman filtering. From the estimated instantaneous frequency, we can measure the time interval between the center frequencies of the incident and the reflected signals. The time interval is the same as the time delay between the incident and the reflected signals. In a simulation assuming that the cable has open fault at the end of the cable, the proposed method showed a good result in estimating the time delay.

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Discrete-Time Robust Guaranteed Cost Filtering for Convex Bounded Uncertain Systems With Time Delay

  • Kim, Jong-Hae
    • Transactions on Control, Automation and Systems Engineering
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    • v.4 no.4
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    • pp.324-329
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    • 2002
  • In this paper, the guaranteed cost filtering design method for linear time delay systems with convex bounded uncertainties in discrete-time case is presented. The uncertain parameters are assumed to be unknown but belonging to known convex compact set of polytotype less conservative than norm bounded parameter uncertainty. The main purpose is to design a stable filter which minimizes the guaranteed cost. The sufficient condition for the existence of filter, the guaranteed cost filter design method, and the upper bound of the guaranteed cost are proposed. Since the proposed sufficient conditions are LMI(linear matrix inequality) forms in terms of all finding variables, all solutions can be obtained simultaneously by means of powerful convex programming tools with global convergence assured. Finally, a numerical example is given to check the validity of the proposed method.

State Encoding of Hidden Markov Linear Prediction Models

  • Krishnamurthy, Vikram;Poor, H.Vincent
    • Journal of Communications and Networks
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    • v.1 no.3
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    • pp.153-157
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    • 1999
  • In this paper, we derive finite-dimensional non-linear fil-ters for optimally reconstructing speech signals in Switched Predic-tion vocoders, Code Excited Linear Prediction(CELP) and Differ-ential Pulse Code Modulation (DPCM). Our filter is an extension of the Hidden Markov filter.

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Design of RFID Air Protocol Filtering and Probabilistic Simulation of Identification Procedure (RFID 무선 프로토콜 필터링의 설계와 확률적 인식 과정 시뮬레이션)

  • Park, Hyun-Sung;Kim, Jong-Deok
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.6B
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    • pp.585-594
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    • 2009
  • Efficient filtering is an important factor in RFID system performance. Because of huge volume of tag data in future ubiquitous environment, if RFID readers transmit tag data without filtering to upper-layer applications, which results in a significant system performance degradation. In this paper, we provide an efficient filtering technique which operates on RFID air protocol. RFID air protocol filtering between tags and a reader has some advantages over filtering in readers and middleware, because air protocol filtering reduces the volume of filtering work before readers and middleware start filtering. Exploiting the air protocol filtering advantage, we introduce a geometrical algorithm for generating air protocol filters and verify their performance through simulation with analytical time models. Results of dense RFID reader environment show that air protocol filtering algorithms reduce almost a half of the total filtering time when compared to the results of linear search.

Robust $H_{\infty}$ filtering for discrete-time polytopic uncertain systems (이산시간 폴리토프형 불확실성 시스템의 견실 $H_{\infty}$ 필터링)

  • Kim, Jong-Hae;Oh, Do-Chang;Lee, Kap-Rai
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.39 no.5
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    • pp.26-33
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    • 2002
  • The design method of robust $H_{\infty}$ filtering for discrete-time uncertain linear systems is investigated in this paper. The uncertain parameters are assumed to be unknown but belonging to known convex compact set of polytope type. The objective is to design a stable robust $H_{\infty}$ filter guaranteeing the asymptotic stability of filtering error dynamics and present an $L_2$ induced norm bound analytically for the modified $H_{\infty}$ performance measure. The sufficient condition for the existence of robust $H_{\infty}$ filter and the filter design method are established by LMI(linear matrix inequality) approach, which can be solved efficiently by convex optimization. The proposed algorithm is checked through an example.

A Filtering Technique of Terrestrial LiDAR Data on Sloped Terrain (사면지형에서 지상라이다 자료의 필터링 기법)

  • Shin, Yoon Su;Choi, Seung Pil;Kim, Jun Seong;Kim, Uk Nam
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.6_1
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    • pp.529-538
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    • 2012
  • By using an algorithm derived by a multiple linear regression analysis, a technique for filtering was developed; and by using the developed technique, the results of conducting filtering of the raw data collected via scanning with a terrestrial LiDAR the actual sloped terrain was analyzed. As such, when filtering was applied by dividing the observation areas into two areas with the topographical line as a reference in order to improve the filtering accuracy, it was seen that the filtering accuracy improved by about 8.73% as compared to when filtering was applied without dividing the observation area. In addition, considering the fact that the accuracy improved by 5~7% when the sloped sides of a multicurvature topography were divided and a complex filtering applied as compared to when filtering was applied for the entire area or by regions, it can be asserted that the accuracy was higher when a complex filtering was conducted by dividing the sloped areas where the slope is not constant due to the multi-curvature of topography.