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電氣學會論文誌. IEEJ Transactions on Electronics, Informa... 51건

  1. [해외논문]   実環境における逐次部分空間推定に基づく移動音源定位  

    Tsuji, Daisuke , Suyama, Kenji
    電氣學會論文誌. IEEJ Transactions on Electronics, Information and Systems. C : 電子·情報·システム v.129 no.1 ,pp. 79 - 86 , 2009 , 0385-4221 ,

    초록

    This paper presents a novel method for moving sound source localization and its performance evaluation in actual room environments. The method is based on the MUSIC (MUltiple SIgnal Classification) which is one of the most high resolution localization methods. When using the MUSIC, a computation of eigenvectors of correlation matrix is required for the estimation. It needs often a high computational costs. Especially, in the situation of moving source, it becomes a crucial drawback because the estimation must be conducted at every the observation time. Moreover, since the correlation matrix varies its characteristics due to the spatial-temporal non-stationarity, the matrix have to be estimated using only a few observed samples. It makes the estimation accuracy degraded. In this paper, the PAST (Projection Approximation Subspace Tracking) is applied for sequentially estimating the eigenvectors spanning the subspace. In the PAST, the eigen-decomposition is not required, and therefore it is possible to reduce the computational costs. Several experimental results in the actual room environments are shown to present the superior performance of the proposed method.

    원문보기

    원문보기
    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지
  2. [해외논문]   周波数領域目的音抽出システムの試作と実環境性能評価  

    Kousaka, Masanori (Department of Electrical and Electronic Engineering, Faculty of Engineering, Tokyo DENKI University ) , Suyama, Kenji (Department of Electrical and Electronic Engineering, Faculty of Engineering, Tokyo DENKI University)
    電氣學會論文誌. IEEJ Transactions on Electronics, Information and Systems. C : 電子·情報·システム v.129 no.1 ,pp. 87 - 93 , 2009 , 0385-4221 ,

    초록

    This paper presents a novel method for moving sound source localization and its performance evaluation in actual room environments. The method is based on the MUSIC (MUltiple SIgnal Classification) which is one of the most high resolution localization methods. When using the MUSIC, a computation of eigenvectors of correlation matrix is required for the estimation. It needs often a high computational costs. Especially, in the situation of moving source, it becomes a crucial drawback because the estimation must be conducted at every the observation time. Moreover, since the correlation matrix varies its characteristics due to the spatial-temporal non-stationarity, the matrix have to be estimated using only a few observed samples. It makes the estimation accuracy degraded. In this paper, the PAST (Projection Approximation Subspace Tracking) is applied for sequentially estimating the eigenvectors spanning the subspace. In the PAST, the eigen-decomposition is not required, and therefore it is possible to reduce the computational costs. Several experimental results in the actual room environments are shown to present the superior performance of the proposed method.

    원문보기

    원문보기
    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지
  3. [해외논문]   周波数領域目的音抽出システムの試作と実環境性能評価  

    Kousaka, Masanori , Suyama, Kenji
    電氣學會論文誌. IEEJ Transactions on Electronics, Information and Systems. C : 電子·情報·システム v.129 no.1 ,pp. 87 - 93 , 2009 , 0385-4221 ,

    초록

    In this paper, we present a realtime implementation of target sound extraction operating in a frequency domain using microphone array and its performance evaluation in actual room environments. In the realized system, the target sound extraction can be achieved by using the FDGSC (Frequency Domain Generalized Sidelobe Canceller) which is one of GSCs. At each the frequency band, the FDGSC is composed of a fixed beamformer part for target sound enhancement and an adaptive filter part for noisy sound reduction. Since the FDGSC is required to perform at every sound data block to apply the DFT (Discrete Fourier Transform), a processing for a series of block data must be completed within a transfer time of block data in the realtime system. Then, we implement the FDGSC using a general purpose DSP (Digital Signal Processor) evaluation board which enable us to perform a high speed signal processing. A superior performance of realtime processing and target sound extraction are shown by several experimental results in the actual room environments.

    원문보기

    원문보기
    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지
  4. [해외논문]   A New Content-Based Image Retrieval Using the Multidimensional Generalization of Wald-Wolfowitz Runs Test  

    Leauhatong, Thurdsak (Graduate School of Science and Technology, Tokai University ) , Hamamoto, Kazuhiko (School of Information and Telecommunication Engineering, Tokai University ) , Atsuta, Kiyoaki (School of Information and Telecommunication Engineering, Tokai University ) , Kondo, Shozo (School of Information and Telecommunication Engineering, Tokai University)
    電氣學會論文誌. IEEJ Transactions on Electronics, Information and Systems. C : 電子·情報·システム v.129 no.1 ,pp. 94 - 102 , 2009 , 0385-4221 ,

    초록

    This paper proposes two new similarity measures for the content-based image retrieval (CBIR) systems. The similarity measures are based on the k -means clustering algorithm and the multidimensional generalization of the Wald-Wolfowitz (MWW) runs test. The performance comparisons between the proposed similarity measures and a current CBIR similarity measure based on the MWW runs test were performed, and it can be seen that the proposed similarity measures outperform the current similarity measure with respect to the precision and the computational time.

    원문보기

    원문보기
    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지
  5. [해외논문]   A New Coarse-To-Fine Method for Computing Disparity Images by Sampling Disparity Spaces  

    Sach, LE Thanh (Graduate School of Science and Technology, Tokai University ) , Hamamoto, Kazuhiko (School of Information and Telecommunication Engineering, Tokai University ) , Atsuta, Kiyoaki (School of Information and Telecommunication Engineering, Tokai University ) , Kondo, Shozo (School of Information and Telecommunication Engineering, Tokai University)
    電氣學會論文誌. IEEJ Transactions on Electronics, Information and Systems. C : 電子·情報·システム v.129 no.1 ,pp. 103 - 111 , 2009 , 0385-4221 ,

    초록

    Image-based 3D reconstruction is a useful and active research area. However, it is a challenge to compute 3D measurements in real-time for high resolution input images even if special hardwares are used. This paper proposes a new coarse-to-fine method that can reduce the computation time of the stereo matching problem. The time reduction is done by sampling disparity spaces and computing the matching costs at only the sampled positions. The disparity map that is derived from a sampled disparity space is used to limit the search region for the finer map to its surrounding region. Because of the sampling of disparity spaces and the limitation of the search region, the computation time is reduced dramatically even if the disparity search range is enlarged significantly. The proposed method has been tested with several public stereo image datasets on the internet. The experimental results indicate that the proposed method can save much of the computation time compared to the other methods that need to compute all of matching costs inside disparity spaces.

    원문보기

    원문보기
    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지
  6. [해외논문]   Fast Incremental Algorithm of Simple Principal Component Analysis  

    Oyama, Tadahiro (Department of Information & Science Intelligent Systems, The University of Tokushima ) , Karungaru, Stephen Githinji (Department of Information & Science Intelligent Systems, The University of Tokushima ) , Tsuge, Satoru (Department of Information & Science Intelligent Systems, The University of Tokushima ) , Mitsukura, Yasue (Graduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Technology ) , Fukumi, Minoru (Department of Information & Science Intelligent Systems, The University of Tokushima)
    電氣學會論文誌. IEEJ Transactions on Electronics, Information and Systems. C : 電子·情報·システム v.129 no.1 ,pp. 112 - 117 , 2009 , 0385-4221 ,

    초록

    This paper presents a new algorithm for incremental learning, which is named Incremental Simple-PCA. This algorithm adds an incremental learning function to the Simple-PCA that is an approximation algorithm of the principal component analysis where an eigenvector can be calculated by a simple repeated calculation. Using the proposed algorithm, it is possible to update the eigenvector faster by using incremental data. We carry out computer simulations on personal authentication that uses face images and wrist motion recognition that uses wrist EMG by incremental learning to verify the effectiveness of this algorithm. These results were compared with the results of Incremental PCA that introduced incremental learning function to the conventional PCA.

    원문보기

    원문보기
    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지
  7. [해외논문]   単語とN-gramの各カテゴリにおける出現頻度の比の和を用いたテキスト自動分類手法  

    Suzuki, Makoto , Hirasawa, Shigeichi
    電氣學會論文誌. IEEJ Transactions on Electronics, Information and Systems. C : 電子·情報·システム v.129 no.1 ,pp. 118 - 124 , 2009 , 0385-4221 ,

    초록

    This paper presents a new algorithm for incremental learning, which is named Incremental Simple-PCA. This algorithm adds an incremental learning function to the Simple-PCA that is an approximation algorithm of the principal component analysis where an eigenvector can be calculated by a simple repeated calculation. Using the proposed algorithm, it is possible to update the eigenvector faster by using incremental data. We carry out computer simulations on personal authentication that uses face images and wrist motion recognition that uses wrist EMG by incremental learning to verify the effectiveness of this algorithm. These results were compared with the results of Incremental PCA that introduced incremental learning function to the conventional PCA.

    원문보기

    원문보기
    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지
  8. [해외논문]   単語とN-gramの各カテゴリにおける出現頻度の比の和を用いたテキスト自動分類手法  

    Suzuki, Makoto , Hirasawa, Shigeichi
    電氣學會論文誌. IEEJ Transactions on Electronics, Information and Systems. C : 電子·情報·システム v.129 no.1 ,pp. 118 - 124 , 2009 , 0385-4221 ,

    초록

    In this paper, we consider the automatic text classification as a series of information processing, and propose a new classification technique, namely, “Frequency Ratio Accumulation Method (FRAM)”. This is a simple technique that calculates the sum of ratios of term frequency in each category. However, it has a desirable property that feature terms can be used without their extraction procedure. Then, we use “character N -gram” and “word N -gram” as feature terms by using this property of our classification technique. Next, we evaluate our technique by some experiments. In our experiments, we classify the newspaper articles of Japanese “CD-Mainichi 2002” and English “Reuters-21578” using the Naive Bayes (baseline method) and the proposed method. As the result, we show that the classification accuracy of the proposed method improves greatly compared with the baseline. That is, it is 89.6% for Mainichi, 87.8% for Reuters. Thus, the proposed method has a very high performance. Though the proposed method is a simple technique, it has a new viewpoint, a high potential and is language-independent, so it can be expected the development in the future.

    원문보기

    원문보기
    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지
  9. [해외논문]   An Improved Hybrid Recommender System Using Multi-Based Clustering Method  

    Puntheeranurak, Sutheera (Graduate School of Engineering, Tokai University ) , Tsuji, Hidekazu (School of Information and Telecommunication Enginerring, Tokai University)
    電氣學會論文誌. IEEJ Transactions on Electronics, Information and Systems. C : 電子·情報·システム v.129 no.1 ,pp. 125 - 132 , 2009 , 0385-4221 ,

    초록

    Recommender systems have become an important research area as they provide some kind of intelligent web techniques to search through the enormous volume of information available on the internet. Content-based filtering and collaborative filtering methods are the most widely recommendation techniques adopted to date. Each of them has both advantages and disadvantages in providing high quality recommendations therefore a hybrid recommendation mechanism incorporating components from both of these methods would yield satisfactory results in many situations. In this paper, we present an elegant and effective framework for combining content-based filtering and collaborative filtering methods. Our approach clusters on user information and item information for content-based filtering to enhance existing user data and item data. Based on the result from the first step, we calculate the predicted rating data for collaborative filtering. We then do cluster on predicted rating data in the last step to enhance the scalability of our proposed system. We call our proposal multi-based clustering method. We show that our proposed system can solve a cold start problem, a sparsity problem, suitable for various situations in real-life applications. It thus contributes to the improvement of prediction quality of a hybrid recommender system as shown in the experimental results.

    원문보기

    원문보기
    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지
  10. [해외논문]   語用情報を含む「論語」知識ベースの構築  

    Yang, Ye (Graduate School of Advanced Technology and Science, The University of Tokushima ) , Tsuchiya, Seiji (Institute of Technology and Science, The University of Tokushima ) , Ren, Fuji (Institute of Technology and Science, The University of Tokushima)
    電氣學會論文誌. IEEJ Transactions on Electronics, Information and Systems. C : 電子·情報·システム v.129 no.1 ,pp. 133 - 139 , 2009 , 0385-4221 ,

    초록

    Recommender systems have become an important research area as they provide some kind of intelligent web techniques to search through the enormous volume of information available on the internet. Content-based filtering and collaborative filtering methods are the most widely recommendation techniques adopted to date. Each of them has both advantages and disadvantages in providing high quality recommendations therefore a hybrid recommendation mechanism incorporating components from both of these methods would yield satisfactory results in many situations. In this paper, we present an elegant and effective framework for combining content-based filtering and collaborative filtering methods. Our approach clusters on user information and item information for content-based filtering to enhance existing user data and item data. Based on the result from the first step, we calculate the predicted rating data for collaborative filtering. We then do cluster on predicted rating data in the last step to enhance the scalability of our proposed system. We call our proposal multi-based clustering method. We show that our proposed system can solve a cold start problem, a sparsity problem, suitable for various situations in real-life applications. It thus contributes to the improvement of prediction quality of a hybrid recommender system as shown in the experimental results.

    원문보기

    원문보기
    무료다운로드 유료다운로드

    회원님의 원문열람 권한에 따라 열람이 불가능 할 수 있으며 권한이 없는 경우 해당 사이트의 정책에 따라 회원가입 및 유료구매가 필요할 수 있습니다.이동하는 사이트에서의 모든 정보이용은 NDSL과 무관합니다.

    NDSL에서는 해당 원문을 복사서비스하고 있습니다. 아래의 원문복사신청 또는 장바구니담기를 통하여 원문복사서비스 이용이 가능합니다.

    이미지

    Fig. 1 이미지

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