• 음성과학
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• 제10권2호
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• pp.57-64
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• 2003

The cepstrum coefficients are the most popular feature for speech recognition or speaker recognition. The cepstrum coefficients are also used for speech synthesis and speech coding but has major drawback of long processing time. In this paper, we proposed a new method that can reduce the processing time of FFT cepstrum analysis. We use the normal ordered inputs for FFT function and the bit-reversed inputs for IFFT function. Therefore we can omit the bit-reversing process and reduce the processing time of FFT ceptrum analysis.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.969-971
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• 1999

Wavelet analysis is applying to many fields such as the time-frequency localization of a time series and a time varying data. In this paper, a statistical testing based Wavelet power spectrum analysis for the stationary Nino3 Sea Surface Temperature(SST) data was executed. Specially, the 95% confidence level for SST was effective in searching the periods of El-Nino using various wavelet basis functions.

• Journal of Mechanical Science and Technology
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• 제19권spc1호
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• pp.429-436
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• 2005

This paper presents a precise and stable time integration method for dynamic analysis of vibration or multibody systems. A total system is divided into several subsystems and their responses are calculated separately, while the coupling effect is treated equivalently as constant force during time steps. By using iterative procedure to improve equivalent coupling forces, a precise and stable solution is obtained. Some examples such as a seismic response and multibody analyses were carried out to demonstrate its usefulness.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제3권10호
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• pp.377-382
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• 2014

모바일 통신과 사물 인터넷(IoT) 환경에서 시간에 따른 데이터의 분석 기술은 주로 의미 있는 정보를 찾기 위해 수집 된 데이터에서 의미있는 패턴을 추출하기 위해 사용된다. 기존의 데이터 마이닝을 이용한 분석 방법은 데이터 수집이 어렵고 시간의 경과와 관련된 시계열 데이터의 변경을 반영하기 위해 완료 상태에 기초하여 해석되어야 한다. 이러한 패턴의 다양성, 대용량성, 연속성 등의 여러 가지 특성을 가진 데이터 스트림의 분석을 위한 방법으로 멀티 블록 스트리밍 데이터 분석(AM-MBSD) 방법을 제안한다. 의미 있는 데이터 추출을 위해 멀티 블록 스트리밍 데이터의 패턴을 추출하고 추출된 연속적 데이터를 여러 개의 블록으로 정의하고 제안 방법의 검증을 위해 각 데이터 블록의 데이터 패턴 생성 시간, 주파수를 수집하고 시계열 데이터를 분석, 실험하였다.

• International Journal of Automotive Technology
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• 제5권4호
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• pp.257-268
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• 2004

The wavelet analysis method is introduced in this paper to study the nonstationary vibration of vehicles. A new road model, a so-called time domain correlated four-wheel road roughness, which considers the coherence relationships between the four wheels of a vehicle, has been newly developed. Based on a vehicle model with eight degrees of freedom, the analysis of nonstationary random vibration responses was carried out in a time domain on a computer. Verification of the simulation results show that the proposed road model is more accurate than previous ones and that the simulated responses are credible enough when compared with some references. Furthermore, by taking wavelet analysis on simulated signals, some substantial rules of vehicle nonstationary vibration, such as the relationship between each vibration level, and how the vibration energy flows on a time-frequency map, beyond those from conventional spectral analysis, were revealed, and these will be of much benefit to vehicle design.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2004년도 추계학술발표대회 논문집
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• pp.47-50
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• 2004

It is very important that the analysis of postbuckling characteristics for stiffened composite structure. Damage tolerance design concept has been imported in many aerospace structures design to increase the structural efficiency and material failure is an inevitable process in postbuckling behavior. These design concepts are very efficient but consume very much calculation time in analytical process. The proper analysis method for reducing calculation time was researched and the total analysis time was reduced. A selection of proper element, the large load increments in linear response region, and the termination of analysis for unnecessary region were imported in the analysis and about $70\%$ time reduction was achieved with keeping a high accuracy of results.

• 동력기계공학회지
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• 제3권1호
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• pp.74-79
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• 1999

This paper describes formulation for algorithm of time historical response analysis of vibration for straight-line structure. This method is derived from a combination of the transfer stiffness coefficient method and the Newmark method. And this present method improves the computational accuracy of the transient vibration response analysis remarkably owing to several advantages of the transfer stiffness coefficient method. We regarded the structure as a lumped mass system here. The analysis algorithm for the time historical response was formulated for the straight-line structure containing crooked, tree type system. The validity of the present method compared with the transfer matrix method and the Finite Element Method for transient vibration analysis is demonstrated through the numerical computations.

• 대한전기학회논문지:전력기술부문A
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• 제55권1호
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• pp.13-17
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• 2006

In this paper, the RCF(Resistive Companion Form) analysis method which is used to analyze small signal stability problems of non-continuous systems including switching devices. The RCF analysis method is mathematically rigorous and computes eigenvalue of the system periodic transition matrix based on discrete system analysis method. As an effect of switching operations, the eigenvalues of the systems are changed and newly unstable oscillation modes may be occurred. As an illustrating example, the oscillation modes of the system with different switching time intervals are computed exactly by the RCF analysis method and the results show that ON/OFF time intervals of switching equipments are important factors to make the system stable or unstable. This result shows that the RCF analysis method is very powerful to analyze small signal stability problems of power systems including switching devices such as FACTS equipments.

• 한국철도학회논문집
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• 제12권6호
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• pp.989-995
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• 2009

Short-time Fourier transforms(STFT)은 시간에 따라 변동하는 조화성분을 가지는 신호의 분석에 유용하게 적용되는 방법이다. 철도차량의 진동신호에서 많이 발견되는 운동학적 진동은 조화 특성이 속도 변화에 따라 점진적으로 변하기 때문에 오더 분석 방법과 상관함수를 이용하면 STFT 분석 방법을 개선할 수 있다. 본 논문에서는 차량의 속도 신호를 구할 수 없거나 잡음이 많을 때 상관함수를 이용하여 신호를 재추출하여 오더 분석을 적용하는 방법에 대하여 다룬다. 이 방법을 한국형고속열차의 운행 중에 취득한 차축 및 차체 진동데이터의 분석에 적용하여 기존의 STFT와 오더 분석을 이용한 방법을 비교 하였다.

• Earthquakes and Structures
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• 제3권6호
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• pp.839-852
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• 2012

Earthquake records are often analyzed in various earthquake engineering problems, making time-frequency analysis for such records of primary concern. The best tool for such analysis appears to be based on wavelet functions; selection of which is not an easy task and is commonly carried through trial and error process. Furthermore, often a particular wavelet is adopted for analysis of various earthquakes irrespective of record's prime characteristics, e.g. wave's magnitude. A wavelet constructed based on records' characteristics may yield a more accurate solution and more efficient solution procedure in time-frequency analysis. In this study, a low-pass reconstruction filter is obtained for each earthquake record based on multi-resolution decomposition technique; the filter is then assigned to be the normalized version of the last approximation component with respect to its magnitude. The scaling and wavelet functions are computed using two-scale relations. The calculated wavelets are highly efficient in decomposing the original records as compared to other commonly used wavelets such as Daubechies2 wavelet. The method is further advantageous since it enables one to decompose the original record in such a way that a clear time-frequency resolution is obtained.