• Title/Summary/Keyword: 특징벡터선택

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Design and Performance Gain Evaluation of a Multi-Rank Codebook Utilizing Statistical Properties of the Spatial Channel Model (공간 채널 모델의 통계적 특성을 반영한 다중 랭크 코드북의 설계 및 성능 이득 평가)

  • Kim, Changhyeon;Sung, Wonjin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.7
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    • pp.723-731
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    • 2016
  • A core technological base to provide enhanced data rates required by 5G mobile wireless communications is the improved bandwidth efficiency using massive multiple-input multiple-output (MIMO) transmission. MIMO transmission requires the channel estimation using the channel state information reference signaling (CSI-RS) and appropriate beamforming, thus the design of the codebook defining proper beamforming vectors is an important issue. In this paper, we propose a multi-rank codebook based on the discrete Fourier transform (DFT) matrix, by utilizing statistical properties of the channel generated by the spatial channel model (SCM). The proposed method includes a structural change of the precoding matrix indicator (PMI) by considering the phase difference distributions between adjacent antenna elements, as well as the selected codevector characteristics of each transmission layer. Performance gain of the proposed method is evaluated and verified by making the performance comparison to the 3GPP standard codebooks adopted by Long-Term Evolution (LTE) systems.

Speech Recognition on Korean Monosyllable using Phoneme Discriminant Filters (음소판별필터를 이용한 한국어 단음절 음성인식)

  • Hur, Sung-Phil;Chung, Hyun-Yeol;Kim, Kyung-Tae
    • The Journal of the Acoustical Society of Korea
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    • v.14 no.1
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    • pp.31-39
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    • 1995
  • In this paper, we have constructed phoneme discriminant filters [PDF] according to the linear discriminant function. These discriminant filters do not follow the heuristic rules by the experts but the mathematical methods in iterative learning. Proposed system. is based on the piecewise linear classifier and error correction learning method. The segmentation of speech and the classification of phoneme are carried out simutaneously by the PDF. Because each of them operates independently, some speech intervals may have multiple outputs. Therefore, we introduce the unified coefficients by the output unification process. But sometimes the output has a region which shows no response, or insensitive. So we propose time windows and median filters to remove such problems. We have trained this system with the 549 monosyllables uttered 3 times by 3 male speakers. After we detect the endpoint of speech signal using threshold value and zero crossing rate, the vowels and consonants are separated by the PDF, and then selected phoneme passes through the following PDF. Finally this system unifies the outputs for competitive region or insensitive area using time window and median filter.

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Data Detection Algorithm Based on GMM in the Acoustic Data Transmission System (음향 데이터 전송 시스템의 강인한 데이터 검출 성능을 위한 Gaussian Mixture Model 기반 연구)

  • Song, Ji-Hyun;Chang, Joon-Hyuk;Kim, Moon-Kee;Kim, Dong-Keon
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.4
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    • pp.136-141
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    • 2011
  • In this paper, we propose an approach to improve the data detection performance of the acoustic data transmission system based on the modulated complex lapped transform (MCLT). We first present an effective analysis of the features and the detection method of data in the acoustic data transmission system. And then feature vectors which are applied to the Gaussian mixture model (GMM) are selected from relevant parameters of the previous system for the efficient data detection. For the purpose of evaluating the performance of the proposed algorithm, Bit error rate (BER) of the received data was measured at different environments (music genres (rock, pop, classic, jazz) and different distances (1m∼5m) from the loudspeaker to the microphone in a office room) and yields better results compared with the conventional scheme of the acoustic data transmission system based on the MCLT.

Combining Support Vector Machine Recursive Feature Elimination and Intensity-dependent Normalization for Gene Selection in RNAseq (RNAseq 빅데이터에서 유전자 선택을 위한 밀집도-의존 정규화 기반의 서포트-벡터 머신 병합법)

  • Kim, Chayoung
    • Journal of Internet Computing and Services
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    • v.18 no.5
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    • pp.47-53
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    • 2017
  • In past few years, high-throughput sequencing, big-data generation, cloud computing, and computational biology are revolutionary. RNA sequencing is emerging as an attractive alternative to DNA microarrays. And the methods for constructing Gene Regulatory Network (GRN) from RNA-Seq are extremely lacking and urgently required. Because GRN has obtained substantial observation from genomics and bioinformatics, an elementary requirement of the GRN has been to maximize distinguishable genes. Despite of RNA sequencing techniques to generate a big amount of data, there are few computational methods to exploit the huge amount of the big data. Therefore, we have suggested a novel gene selection algorithm combining Support Vector Machines and Intensity-dependent normalization, which uses log differential expression ratio in RNAseq. It is an extended variation of support vector machine recursive feature elimination (SVM-RFE) algorithm. This algorithm accomplishes minimum relevancy with subsets of Big-Data, such as NCBI-GEO. The proposed algorithm was compared to the existing one which uses gene expression profiling DNA microarrays. It finds that the proposed algorithm have provided as convenient and quick method than previous because it uses all functions in R package and have more improvement with regard to the classification accuracy based on gene ontology and time consuming in terms of Big-Data. The comparison was performed based on the number of genes selected in RNAseq Big-Data.

A Study of Textured Image Segmentation using Phase Information (페이즈 정보를 이용한 텍스처 영상 분할 연구)

  • Oh, Suk
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.2
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    • pp.249-256
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    • 2011
  • Finding a new set of features representing textured images is one of the most important studies in textured image analysis. This is because it is impossible to construct a perfect set of features representing every textured image, and it is inevitable to choose some relevant features which are efficient to on-going image processing jobs. This paper intends to find relevant features which are efficient to textured image segmentation. In this regards, this paper presents a different method for the segmentation of textured images based on the Gabor filter. Gabor filter is known to be a very efficient and effective tool which represents human visual system for texture analysis. Filtering a real-valued input image by the Gabor filter results in complex-valued output data defined in the spatial frequency domain. This complex value, as usual, gives the module and the phase. This paper focused its attention on the phase information, rather than the module information. In fact, the module information is considered very useful at region analysis in texture, while the phase information was considered almost of no use. But this paper shows that the phase information can also be fully useful and effective at region analysis in texture, once a good method introduced. We now propose "phase derivated method", which is an efficient and effective way to compute the useful phase information directly from the filtered value. This new method reduces effectively computing burden and widen applicable textured images.

Autoregressive Modeling in Orthogonal Cutting of Glass Fiber Reinforced Composites (2차원 GFRC절삭에서 AR모델링에 관한 연구)

  • Gi Heung Choi
    • Journal of the Korean Society of Safety
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    • v.16 no.1
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    • pp.88-93
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    • 2001
  • This study discusses frequency analysis based on autoregressive (AR) time series model, and process characterization in orthogonal cutting of a fiber-matrix composite materials. A sparsely distributed idealized composite material, namely a glass reinforced polyester (GFRP) was used as workpiece. Analysis method employs a force sensor and the signals from the sensor are processed using AR time series model. The resulting pattern vectors of AR coefficients are then passed to the feature extraction block. Inside the feature extraction block, only those features that are most sensitive to different types of cutting mechanisms are selected. The experimental correlations between the different chip formation mechanisms and AR model coefficients are established.

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A Study on Isolated Words Speech Recognition in a Running Automobile (주행중인 자동차 환경에서의 고립단어 음성인식 연구)

  • 유봉근
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1998.06e
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    • pp.381-384
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    • 1998
  • 본 논문은 주행중인 자동차 환경에서 운전자의 안전성 및 편의성의 동시 확보를 위하여, 보조적인 스위치 조작없이 상시 음성의 입, 출력이 가능하도록 한다. 이때 잡음에 강인한 threshold 값을 구하기 위하여, 일정한 시간마다 기준 에너지와 영교차율(Zero Crossing Rate)을 변경하며, 밴드패스 필터(bandpass filter)를 이용하여 1차, 2차로 나누어 실시간 상태에서 자동으로, 정확하게 끝점검출(End Point Detection)을 처리한다. 기준패턴(reference pattern)은 DMS(Dynamic Multi-Section)을 사용하며, 화자의 변별력을 높이기 위하여 2개의 모델사용을 제안한다. 또한 주행중인 차량의 잡음환경에 강인하기 위하여 일반주행(80km/h 이내), 고속주행(80km/h 이상)등으로 나누며 차량의 가변잡음 크기에 따라 자동으로 선택하도록 한다. 음성의 특징 벡터와 인식 알고리즘은 PLP 13차와 One-Stage Dynamic Programming (OSDP)를 이용한다. 실험결과, 자주 사용되는 차량 편의장치 제어명령 33개에 대하여 중부, 영동 고속도로(시속 80Km/h 이상)에서 화자독립 89.75%, 화자종속 90.08%의 인식율을 구하였으며, 경부 고속도로에서는 화자독립 92.29%, 화자종속 92.42%의 인식율을 구하였다. 그리고 저속 주행중인 자동차 환경(80km/h 이내, 시멘트, 아스팔트 등의 서울시내 및 시외독립)에서는 화자독립 92.89%, 화자종속 94.44% 인식율을 구하였다.

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Human Iris Recognition System using Wavelet Transform and LVQ (웨이브렛 변환과 LVQ를 이용한 홍채인식 시스템)

  • Lee, Gwan-Yong;Im, Sin-Yeong;Jo, Seong-Won
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.7
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    • pp.389-398
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    • 2000
  • The popular methods to check the identity of individuals include passwords and ID cards. These conventional method for user identification and authentication are not altogether reliable because they can be stolen and forgotten. As an alternative of the existing methods, biometric technology has been paid much attention for the last few decades. In this paper, we propose an efficient system for recognizing the identity of a living person by analyzing iris patterns which have a high level of stability and distinctiveness than other biometric measurements. The proposed system is based on wavelet transform and a competitive neural network with the improved mechanisms. After preprocessing the iris data acquired through a CCD camera, feature vectors are extracted by using Haar wavelet transform. LVQ(Learning Vector Quantization) is exploited to classify these feature vectors. We improve the overall performance of the proposed system by optimizing the size of feature vectors and by introducing an efficient initialization of the weight vectors and a new method for determining the winner in order to increase the recognition accuracy of LVQ. From the experiments, we confirmed that the proposed system has a great potential of being applied to real applications in an efficient and effective way.

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Improving the Performance of a Speech Recognition System in a Vehicle by Distinguishing Male/Female Voice (성별 구별방법에 의한 자동차 내 음성 인식 성능 향상)

  • Yang, Jin-Woo;Kim, Sun-Hyeop
    • Journal of KIISE:Software and Applications
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    • v.27 no.12
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    • pp.1174-1182
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    • 2000
  • 본 논문은 주행중인 자동차 환경에서 운전자의 안전성 및 편의성의 동시 확보를 위하여, 보조적인 스위치 조작 없이 상시 음성의 입, 출력이 가능한 시스템을 제안하였다. 이대 잡음에 강인한 threshold 값을 구하기 위하여, 1.5초마다 기준 에너지와 영 교차율을 변경하였으며 대역 통과 여과기를 이용하여 1차, 2차로 나누어 실시간 상태에서 자동으로, 정확하게 끝점 검출을 처리하였다. 또한 남성, 여성을 피치검출로 구분하여 모델을 선택하게 하였고, 주행중인 자동차 속도에 따라 가장 적합한 모델을 사용하기 위하여 Idle-40km, 40-80km, 80-100km로 구분하여 남성, 여성 모델을 각각 구분하여 인식할 수 있게 하였다. 그리고, 음성의 특징 벡터와 인식 알고리즘은 PLP 13차와 OSDP(one-Stage Dynamic Programming)을 사용하였다. 본 실험은 서울시내 도로 및 내부 순환도로에서 각각 속도별로 구분하여 화자독립 인식 실험을 한 결과 40-80km 상태에서 남자는 96.8%, 여자는 95.1%, 80-100km 상태에서는 남자 91.6%, 여자는 90.6%의 인식결과를 얻을 수 있었고, 화자종속 인식실험 결과 40-80km 상태에서 남자는 98%, 여자는 96%, 80-100km 상태에서는 남자는 96%, 여자는 94%의 높은 인식률을 얻었으므로, system의 유효성을 입증하였다.

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A Study on the Dual Video Watermarking for Authentication and Signature using DC/AC Components of Block Layer (블록계층의 DC/AC 성분을 이용한 인증과 서명의 이중 비디오 워터마킹에 관한 연구)

  • Boo, Hee-Hyung;Park, Seong-Mi;Bae, Ho-Young;Lee, Bae-Ho
    • Annual Conference of KIPS
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    • 2005.11a
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    • pp.743-746
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    • 2005
  • 본 논문에서는 디지털 비디오 인코딩 과정의 VLC(variable length coding) 영역에서 블록계층의 DC/AC 성분을 이용한 인증과 서명의 이중 비디오 워터마킹 시스템을 제안하였다. 제안한 기법은 블록계층의 DC 성분과 AC 성분에서 HVS(human visual system)의 특성을 고려한 것이다. 인증 워터마킹은 주요한 정보를 포함하는 저주파 영역과 윤곽선 정보를 포함하는 중간 주파수 영역을 이용하여 인트라 프레임의 DC 성분과 움직임 벡터의 부호를 변형시켰고, 서명 워터마킹은 모든 프레임의 AC 성분들 중에서 마지막 AC 성분의 Level이 '1'인 경우에만 워터마크를 삽입하였다. 서명 워터 마크 검출은 저작권자의 비밀 키에 의해서만 가능하고, 기술적인 면에서 저자권자의 판별 기준이 될 수 있다. 제안한 이중 비디오 워터마킹 시스템의 특징은 인증과 서명의 두 가지 기능을 선택적으로 수행할 수 있으며, 계산과정이 복잡하지 않으면서 비트 스트림(bit-stream)을 유지시킨다. 그리고 실험 결과에서 기존의 방법보다 화질 면에서 $2{\sim}3dB$ 더 높은 수치를 얻어 우수함을 보였고, 인코딩 수행 속도에 미치는 영향은 거의 없었으며, 향후 실시간 인코딩 처리에 응용될 수 있다.

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