• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2016년도 하계학술대회
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• pp.80-81
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• 2016

본 논문에서는 딥 러닝을 이용한 오디오 장르 분류 기술을 제안한다. 장르는 music, speech, effect 3가지로 정의하여 분류한다. 기존의 GMM을 이용한 장르 분류 기술은 speech의 인식률에 비해 music과 effect에 대한 인식률이 낮아 각 장르에 대한 인식률의 차이를 보인다. 이러한 문제를 해결하기 위해 본 논문에서는 딥 러닝을 이용해 높은 수준의 추상화 과정을 거쳐 더 세분된 학습을 진행한다. 제안한 방법을 사용하면 미세한 차이의 특성까지 학습해 장르에 대한 인식률의 차이를 줄일 수 있으며, 각 장르에 대해 GMM을 이용한 오디오 장르 분류보다 높은 인식률을 얻을 수 있다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2012년도 춘계학술대회
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• pp.59-61
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• 2012

TDOA 기법은 위치추정 기법의 하나로 간단한 구조와 높은 정확도를 가지는 장점으로 인해 실내측위, 군사, 의료 분야 등에 자주 사용된다. 본 논문에서는 MPM(Matrix Pencil Method)를 이용한 고분해능 TDOA 추정 기법을 제안한다. 제안된 기법은 기존의 교차상관을 이용한 TDOA 기법에 비교하여 높은 정확도를 가지며 CW(Continuous Wave)와 같은 협대역 신호에 적용이 가능하다. 또한 잘 알려진 고분해능 기법 중 하나인 MUSIC(Multiple Signal Classification)에서 공분산 행렬을 사용하는 것과 달리 수집된 데이터를 바로 행렬로 만들어 사용하므로 복잡성이 낮은 특징이 있다. 제안된 기법의 성능을 검증하기 위해 소프트웨어 시뮬레이션 통해 SNR에 따른 오차와 연산량 측면에서 MUSIC 기법과 비교하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문집
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• pp.699-704
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• 2002

A method using beamforming algorithm has been developed to measure oblique incidence reflection coefficients of sound absorption materials. MUSIC(Multiple Signal Classification) method detects the angles of incidence and reflection. By separating the incident and reflected waves using beamforming method, the reflection coefficient is calculated. Spatial smoothing technique is also used to reduce the coherence between the incident and reflected waves. The test materials were modeled as a locally reacting surface. Numerical and experiment results are performed to verify the acuracy of proposed method.

• 한국전자파학회:학술대회논문집
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• 한국전자파학회 2002년도 종합학술발표회 논문집 Vol.12 No.1
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• pp.44-48
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• 2002

This paper describes an adaptive signal processing of digital receiver with DDC(Digital Down Convertor), DDC is implemented by using NCO(Numerically Controlled Oscillator), digital low pass filter. for the passband sampling, we present the results of digital receiver simulation with DDC. We confirm that the low IP signal is converted to zero IF by DDC. DOA(Direction Of Arrival) estimation technique using MUSIC(Multiple SIgnal Classification) algorithm with high resolution is presented. We Cow that an accurate resolution of DOA depends on the input sampling number.

• 한국소음진동공학회논문집
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• 제13권6호
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• pp.438-444
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• 2003

A method using beamforming algorithm has been developed to measure oblique incidence reflection coefficients of sound absorption materials. MUSIC(multiple signal classification) method detects the angles of incidence and reflection. By separating the incident and reflected waves using beamforming method, the reflection coefficient is calculated. Spatial smoothing technique Is also used to reduce the coherence between the incident and reflected waves. Numerical and experiment results are performed to verify the accuracy of proposed method.

• 한국소음진동공학회논문집
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• 제11권6호
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• pp.200-207
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• 2001

In this paper, a new method for Partial field decomposition is developed that is based on the beamforming algorithm for the application of acoustical holography to a composite sound field generated by multiple incoherent sound sources. In the proposed method, source Positions are first predicted by MUSIC(multiple signal classification) algorithm. The composite sound fields can then be decomposed into each partial field by the beamforming. Results of both numerical simulations and experiments show that the method can find each partial field very accurately and effectively, and that it also has Potential to be used for application to distributed sources.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2019년도 제59차 동계학술대회논문집 27권1호
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• pp.243-246
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• 2019

본 논문에서는 감성과 힐링, 머신러닝이라는 주제를 바탕으로 딥러닝을 통한 사용자의 얼굴표정을 인식하고 그 얼굴표정을 기반으로 음악을 재생해주는 얼굴표정 기반의 음악재생 프로그램을 제안한다. 얼굴표정 기반 음악재생 프로그램은 딥러닝 기반의 음악 프로그램으로써, 이미지 인식 분야에서 뛰어난 성능을 보여주고 있는 CNN 모델을 기반으로 얼굴의 표정을 인식할 수 있도록 데이터 학습을 진행하였고, 학습된 모델을 이용하여 웹캠으로부터 사용자의 얼굴표정을 인식하는 것을 통해 사용자의 감정을 추측해낸다. 그 후, 해당 감정에 맞게 감정을 더 증폭시켜줄 수 있도록, 감정과 매칭되는 노래를 재생해주고, 이를 통해, 사용자의 감정이 힐링 및 완화될 수 있도록 도움을 준다.

• Journal of Positioning, Navigation, and Timing
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• 제10권2호
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• pp.131-137
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• 2021

The Angle-of-Arrival (AOA) estimation in real time is one of core technologies for the real-time tracking system, such as a radar or a satellite. Although AOA estimation algorithms for various antenna types have been studied, most of them are for the single-shaped array antenna suitable to the specific frequency. In this paper, we propose the cascade AOA estimation algorithm for the combined array antenna with Uniform Rectangular Frame Array (URFA) and Uniform Circular Array (UCA), with the excellent performance for various frequencies. The proposed technique is consisted of Capon for roughly finding AOA groups with multiple signal AOAs and Beamspace Multiple Signal Classification (MUSIC) for estimating the detailed signal AOA in the AOA group, for the combined array antenna. In addition, we provide computer simulation results for verifying the estimation performance of the proposed algorithm.

• Journal of Positioning, Navigation, and Timing
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• 제11권2호
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• pp.91-98
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• 2022

In the next generation wireless communication system, the beamforming technique based on a massive antenna is one of core technologies for transmitting and receiving huge amounts of data, efficiently and accurately. For highly performed and highly reliable beamforming, it is required to accurately estimate the Angle of Arrival (AOA) for the desired signal incident to an antenna. Employing the massive antenna with a large number of elements, although the accuracy of the AOA estimation is enhanced, its computational complexity is dramatically increased so much that real-time communication is difficult. In order to improve this problem, AOA estimation algorithms based on the massive antenna with the low computational complexity have been actively studied. In this paper, we compute and analyze the computational complexity of the cascade AOA estimation algorithm based on the Flexible Massive Concentric Circular Array (FMCCA). In addition, its computational complexity is compared to conventional AOA estimation techniques such as the Multiple Signal Classification (MUSIC) algorithm with the high resolution and the Only Beamspace MUSIC (OBM) algorithm.

• Journal of Information Processing Systems
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• 제18권3호
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• pp.293-301
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• 2022

Direction of arrival (DOA) estimation of space signals is a basic problem in array signal processing. DOA estimation based on the multiple signal classification (MUSIC) algorithm can theoretically overcome the Rayleigh limit and achieve super resolution. However, owing to its inadequate real-time performance and accuracy in practical engineering applications, its applications are limited. To address this problem, in this study, a DOA estimation algorithm with high parallelism and precision based on an analysis of the characteristics of complex matrix eigenvalue decomposition and the coordinate rotation digital computer (CORDIC) algorithm is proposed. For parallel and single precision, floating-point numbers are used to construct an orthogonal identity matrix. Thus, the efficiency and accuracy of the algorithm are guaranteed. Furthermore, the accuracy and computation of the fixed-point algorithm, double-precision floating-point algorithm, and proposed algorithm are compared. Without increasing complexity, the proposed algorithm can achieve remarkably higher accuracy and efficiency than the fixed-point algorithm and double-precision floating-point calculations, respectively.