• 한국음향학회지
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• 제21권3호
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• pp.304-309
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• 2002

LSP (Line Spectrum Pairs) 파라미터는 음성코덱 (codec)이나 인식기에서 음성신호를 분석하여 전송형이나 저장형 파라미터로 변환되어, 주로 저전송률 음성부호화기에 사용된다. 그러나 LPC (Linear Predictive Coding) 계수를 LSP로 변환하는 방법이 복잡하여 계산시간이 많이 소요된다는 단점이 있다. 기존의 LSP변환 방법 중 음성 부호화기에서 주로 사용하는 실근 (real root)방법은 근을 구하기 위해 주파수 영역을 순차적으로 검색하기 때문에 계산시간이 많이 소요되는 단점을 갖는다. 본 논문에서 기존의 실근 방법과 비교 평가한 알고리즘은 첫 번째 검색 대역에 멜 스케일 (met scale)을 사용하였고, 두 번째는 LSP 파라미터의 분포 특성을 조사하여 이를 토대로 검색구간의 순서와 검색간격을 달리 하였다. 실험결과, 기존의 실근 방식에 비하여 두 가지 방식 모두가 변환시간의 47% 이상이 감소되는데 반하여 동일한 근을 찾음을 알 수가 있었다.

• Journal of Mechanical Science and Technology
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• 제15권8호
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• pp.1090-1096
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• 2001

In this paper, new methods for efficiently solving linear acceleration equations of multibody dynamic simulation exploiting sparsity for real-time simulation are presented. The coefficient matrix of the equations tends to have a large number of zero entries according to the relative joint coordinate numbering. By adequate joint coordinate numbering, the matrix has minimum off-diagonal terms and a block pattern of non-zero entries and can be solved efficiently. The proposed methods, using sparse Cholesky method and recursive block mass matrix method, take advantages of both the special structure and the sparsity of the coefficient matrix to reduce computation time. The first method solves the η$\times$η sparse coefficient matrix for the accelerations, where η denotes the number of relative coordinates. In the second method, for vehicle dynamic simulation, simple manipulations bring the original problem of dimension η$\times$η to an equivalent problem of dimension 6$\times$6 to be solved for the accelerations of a vehicle chassis. For vehicle dynamic simulation, the proposed solution methods are proved to be more efficient than the classical approaches using reduced Lagrangian multiplier method. With the methods computation time for real-time vehicle dynamic simulation can be reduced up to 14 per cent compared to the classical approach.

• Journal of Information Technology Applications and Management
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• 제24권1호
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• pp.157-167
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• 2017

This paper proposes a simple sound source localization (SSL) method based on signal energies comparison and partial cross correlation for TDOA computation. Many sound source localization methods include multiple TDOA computations in order to eliminate front-back confusion. Multiple TDOA computations however increase the methods' computation times which need to be as minimal as possible for real-time applications. Our aim in this paper is to achieve the same results of localization using fewer computations. Using three microphones, we first compare signal energies to predict which quadrant the sound source is in, and then we use partial cross correlation to estimate the TDOA value before computing the azimuth value. Also, we apply a threshold value to reinforce our prediction method. Our experimental results show that the proposed method has less computation time; spending approximately 30% less time than previous three microphone methods.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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• pp.405-408
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• 2002

LSP(Line Spectrum Pairs) Parameter is used for speech analysis in vocoders or recognizers since it has advantages of constant spectrum sensitivity. low spectrum distortion and easy linear interpolation. However the method of transforming LPC(Linear Predictive Coding) into LSP is so complex that it takes much time to compute. Among conventional methods, the real root method is considerably simpler than others, but nevertheless, it still suffers from its jndeterministic computation time because the root searching is processed sequentially in frequency region. We suggest a method of reducing the LSP transformation time using voice characteristics The proposed method is to apply search order and interval differently according to the distribution of LSP parameters. in comparison with the conventional real root method, the proposed method results in about 46.5% reduction. And, the total computation time is reduce to about 5% in the G.723.1 vocoder.

• 한국멀티미디어학회논문지
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• 제18권11호
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• pp.1289-1301
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• 2015

Pedestrian detection (PD) is an essential task in various applications and sliding window-based methods utilizing HOG (Histogram of Oriented Gradients) or HOG-like descriptors have been shown to be very effective for accurate PD. However, due to exhaustive search across images, PD methods based on sliding window usually require heavy computational time. In this paper, we propose a real-time PD method for embedded visual surveillance with fixed backgrounds. The proposed PD method employs HOG descriptors as many PD methods does, but utilizes selective search so that it can save processing time significantly. The proposed selective search is guided by restricting searching to candidate regions extracted from Adaptive Gaussian Mixture Model (AGMM)-based background subtraction technique. Moreover, approximate computation of HOG descriptor and implementation in fixed-point arithmetic mode contributes to reduction of processing time further. Possible accuracy degradation due to approximate computation is compensated by applying an appropriate one among three offline trained SVM classifiers according to sizes of candidate regions. The experimental results show that the proposed PD method significantly improves processing speed without noticeable accuracy degradation compared to the original HOG-based PD and HOG with cascade SVM so that it is a suitable real-time PD implementation for embedded surveillance systems.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2451-2454
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• 2003

In this paper, we propose the computation reduction methods of LSP(Line spectrum pairs) transformation that is mainly used in CELP vocoders. In order to decrease the computational time in real root method the characteristic of four proposed algorithms is as the following. First, scheme to reduce the LSP transformation time uses met scale. Developed the second scheme is the control of searching order by the distribution characteristic of LSP parameters. Third, scheme to reduce the LSP transformation time uses voice characteristics. Developed the fourth scheme is the control of searching interval and order by the distribution characteristic of LSP parameters. As a result of searching time, computational amount, transformed LSP parameters, SNR, MOS test, waveform of synthesized speech, speech, spectrogram analysis, searching time reduced about 37.5％, 46.21％, 46.3％, 51.29％ in average, computational amount is reduced about 44.76％, 49.44％, 47.03％, 57.40％. But the transformed LSP parameters of the proposed methods were the same as those of real root method.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2010년도 춘계학술발표논문집 1부
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• pp.257-260
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• 2010

In this paper, we propose the computation reduction methods of LSP(Line spectrum pairs) transformation that is mainly used in CELP vocoders. In order to decrease the computational time in real root method the characteristic of four proposed algorithms is as the following. First, scheme to reduce the LSP transformation time uses mel scale. Developed the second scheme is the control of searching order by the distribution characteristic of LSP parameters. Third, scheme to reduce the LSP transformation time uses voice characteristics. Developed the fourth scheme is the control of searching interval and order by the distribution characteristic of LSP parameters. As a result of searching time, computational amount, transformed LSP parameters, SNR, MOS test, waveform of synthesized speech, spectrogram analysis, searching time is reduced about 37.5%, 46.21%, 46.3%, 51.29% in average, computational amount is reduced about 44.76%, 49.44%, 47.03%, 57.40%. But the transformed LSP parameters of the proposed methods were the same as those of real root method.

• 한국정보통신학회논문지
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• 제14권11호
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• pp.2478-2484
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• 2010

본 논문은 실시간 파노라마를 위한 영상의 특징점 검출 방법을 제안한다. 파노라마 연구는 최근 실시간 지역탐색이나 DVR 등에 적용하는 연구가 최근 활발히 진행되고 있다. 특히 특징점 검출은 파노라마를 이루는 가장 중요한 요소이다. 특징점 검출을 위해서는 어떠한 명암 변화에도 특징점은 불변이어야 하며 이미지의 크기와 회전이 변화하더라도 불변의 점을 찾아야 한다. 기존 연구방법은 고차원적인 벡터와 많은 후보점을 선점하기 때문에 연산량이 많고 수행시간이 길어 실시간에 활용하기에는 어려운 점이 있다. 따라서 본 논문은 보다 빠른 실시간 특징점 검출을 위해 LOG 방법을 비트 단위로 분할 후 결합하는 BLOG 방법을 제안하고 다양한 실험을 통하여 속도와 연산량 그리고 검출 성능에 대하여 비교한다.

• Journal of Power Electronics
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• 제11권2호
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• pp.202-210
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• 2011

Polymer electrolyte membrane (PEM) fuel cell is one of the popular renewable energy sources and widely used in commercial medium power areas from portable electronic devices to electric vehicles. In addition, the increased integration of the PEM fuel cell with power electronics, dynamic loads, and control systems requires accurate electrical models and simulation methods to emulate their electrical behaviors. Advancement in parallel computation techniques, various real-time simulation tools, and smart power hardware have allowed the prototyping of novel apparatus to be investigated in a virtual system under a wide range of realistic conditions repeatedly, safely, and economically. This paper builds up advancements of optimized model constructions for a fuel cell stack system on a real-time simulator in the view points of improving dynamic model accuracy and boosting computation speed. In addition, several considerations for a power hardware-in-the-loop (PHIL) simulation are provided to electrically emulate the PEM fuel cell stack system with power facilities. The effectiveness of the proposed PHIL simulation method developed on Opal RT's RT-Lab Matlab/Simulink based real-time engineering simulator and a programmable power supply is verified using experimental results of the proposed PHIL simulation system with a Ballard Nexa fuel cell stack.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2005년도 학술발표회 논문집
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• pp.62-67
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• 2005

A new picking algorithm has been developed on real-time basis for finding the onset of P wave as well as discriminating the micro seismic signal from artificial noise. Unlike the previous methods which have used the STA/LTA ratio for discriminating the P arrivals, we have adopted the slope discrimination methods for identifying the P onset. As result, this algorithm has been turned out to be efficient in both accuracy and computation in on-line system.