• 대한기계학회논문집
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• 제18권4호
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• pp.1057-1063
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• 1994

An instantaneous frequency analysis is a technique to examine a signature for the rotating machinery if the signal has several transitions within a cycle. This paper discusses the conditions of existing negative frequency components in the instantaneous frequency. By using a signal consisted of two frequency components, the instantaneous frequency analysis is conducted while the amplitude ratio between two frequency components has been changed. The analysis shows that, depending on the amplitude ratio, the instantaneous frequencies have averaged, zero-valued, or negative components. It turns out that the negative-valued instantaneous frequencies, which have been regarded as the noise effect, are the consequence of the calculation process for the multisignal components. The criteria of existing the negative values in instantaneous frequencies is given in terms of the relative amplitude ratio and the frequency difference. Especially when the amplitude ratio approaches to 1, the instantaneous frequency fluctuates ${\pm}\infty$ in theory, which implies that instantaneous frequency has unstable region around the amplitude ratio, 1.Also, as the frequency difference between major signal components is increased, the region of existing negative instantaneous becomes broader. In an instantaneous frequency analysis, therefore, a narrow band analysis is suggested, with extreme care if the amplitude ratio approaches to 1. In this paper, a vibration signal monitored from a rotating machinery is also examined as an application example in order to show the existence of negative instantaneous frequencies components.

• Journal of Astronomy and Space Sciences
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• 제28권4호
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• pp.261-265
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• 2011

We investigate the sunspot area data spanning from solar cycles 1 (March 1755) to 23 (December 2010) in time domain. For this purpose, we employ the Hilbert transform analysis method, which is used in the field of information theory. One of the most important advantages of this method is that it enables the simultaneous study of associations between the amplitude and the phase in various timescales. In this pilot study, we adopt the alternating sunspot area as a function of time, known as Bracewell transformation. We first calculate the instantaneous amplitude and the instantaneous phase. As a result, we confirm a ~22-year periodic behavior in the instantaneous amplitude. We also find that a behavior of the instantaneous amplitude with longer periodicities than the ~22-year periodicity can also be seen, though it is not as straightforward as the obvious ~22-year periodic behavior revealed by the method currently proposed. In addition to these, we note that the phase difference apparently correlates with the instantaneous amplitude. On the other hand, however, we cannot see any obvious association of the instantaneous frequency and the instantaneous amplitude. We conclude by briefly discussing the current status of development of an algorithm for the solar activity forecast based on the method presented, as this work is a part of that larger project.

• 음성과학
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• 제12권4호
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• pp.53-70
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• 2005

A Vowel of speech signals are multicomponent signals composed of AM-FM components whose instantaneous frequency and instantaneous amplitude are time-varying. The changes of emotion states cause the variation of the instantaneous frequencies and the instantaneous amplitudes of AM-FM components. Therefore, it is important to estimate exactly the instantaneous frequencies and the instantaneous amplitudes of AM-FM components for the extraction of key information representing emotion states and changes in speech signals. In tills paper, firstly a method decomposing speech signals into AM - FM components is addressed. Secondly, the fundamental frequency of vowel sound is estimated by the simple method based on the spectrogram. The estimate of the fundamental frequency is used for decomposing speech signals into AM-FM components. Thirdly, an estimation method is suggested for separation of the instantaneous frequencies and the instantaneous amplitudes of the decomposed AM - FM components, based on Hilbert transform and the demodulation property of the extended Fourier transform. The estimates of the instantaneous frequencies and the instantaneous amplitudes can be used for modification of the spectral distribution and smooth connection of two words in the speech synthesis systems based on a corpus.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권2호
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• pp.162-166
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• 2012

The instantaneous amplitude (IA) based on the higher order differential energy operator is proposed. And its general form for arbitrary order is also proposed. The various definitions of the IA and the instantaneous frequency (IF) estimators are considered. The IA and IF estimators based on the energy operators need less computational cost than the conventional IF and IA estimators exploiting the Hilbert transform. The IF and IA estimators are compared in terms of the frequency and amplitude tracking accuracy of the AM-FM signals. For noiseless case, the IA and IF estimators based on the Teager-Kaiser energy operator show better tracking performance than the IF and IA estimators based on the higher energy operators. However, under noisy condition, the IF and IA estimator based on the higher order energy operators with the order 3 and 4 show better tracking than the Teager-Kaiser energy based estimators. The IF and IA estimators are applied to signals in the various power anomalies to show their usefulness as the disturbance detectors.

• 전기학회논문지
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• 제61권8호
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• pp.1193-1198
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• 2012

An instantaneous amplitude (IA) estimator using the symmetric higher order differential energy operator is proposed. The amplitude estimator and the instantaneous frequency (IF) estimator based on the symmetric higher order differential energy operator coincide with the analyzed signal in time, and they show better estimation results than the IA and IF based on the higher order differential energy operator. Various IF and IA estimators are applied to AM-FM signals for the performance comparison. Among the IF and IA estimators, the IF and IA estimators based on the symmetric higher order energy operator show the best estimation accuracy. Then, the IA and IF estimators are applied to the distorted power line signal to show their usefulness as power disturbance detectors.

• 지구물리와물리탐사
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• 제4권4호
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• pp.115-123
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• 2001

탄성파 중합 단면도 상에서 천연가스 부존 여부를 지시하는 명점(bright spot)은 가스 층이외에 음향계수 차이가 큰 지층에서도 나타나므로 가스 층여부를 판단하기 위해서는 속도분석, AVO 분석, 탄성파 복소 트레이스 분석 등 추가적인 정밀 자료처리가 필요하다. 본 연구에서는 가스 층 추정을 위해 정밀 속도분석과 트레이스 복소분석 그리고 입사각에 따른 진폭변화 결과인 탄화수소 직접 지시 단면도(DHI)분석을 실시하였다. 트레이스 복소분석은 지층 상$\cdot$하간의 물성변화에 따른 지질정보를 제공하는것으로 여기에서는 순간 진폭, 순간 진폭에 대한 1차 및 2차 미분 값, 순간 위상, 순간 주파수, 가중평균 순간 주파수 값을 구하여 시추가 이루어진 국내 대륙붕 탄성파 자료에 적용하였다. 자료처리 결과 가스가 부존할 가능성이 높은 지역에서는 순간 진폭, 순간 주파수 단면도 그리고 AVO 분석에 의한 DHI 단면도에서 공통적으로 탄성파 진폭이상이 나타나며 정밀 자료처리 결과 중 어느 한 곳이라도 진폭이상이 나타나지 않으면 가스 부존 가능성이 낮다고 할 수 있다.

• 음성과학
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• 제12권4호
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• pp.17-29
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• 2005

Time-frequency representation reveals some useful information about instantaneous frequency, instantaneous bandwidth and boundary of each AM-FM component of a speech signal. In many cases, the instantaneous frequency of each component is not constant. The variability of instantaneous frequency causes degradation of resolution in time-frequency representation. This paper presents a method of adaptively adjusting the transform kernel for preventing degradation of resolution due to time-varying instantaneous frequency. The transform kernel is the form of frequency modulated function. The modulation function in the transform kernel is determined by the estimate of instantaneous frequency which is approximated by first order polynomial at each time instance. Also, the window function is modulated by the estimated instantaneous. frequency for mitigation of fringing. effect. In the proposed method, not only the transform kernel but also the shape and the length of. the window function are adaptively adjusted by the instantaneous frequency of a speech signal.

• Journal of Electrical Engineering and Technology
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• 제5권1호
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• pp.140-145
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• 2010

The monitoring and the diagnosis of the faults in induction motors starting from the stator current are very interesting, since it is an accessible and measurable quantity. The spectral analysis of the stator current makes it possible to highlight the characteristic frequencies of the faults but in a wide frequency range depending on half the sampling frequency, making it very difficult to monitor on-line the faults. In order to facilitate the use of the relevant frequencies of machine faults we proposed the extraction of the frequency components using two methods, namely, the amplitude and the instantaneous frequency. The theoretical bases of these methods were presented and the results were validated on a test bench with an induction motor of 5.5 kw.

• 음성과학
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• 제8권4호
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• pp.45-58
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• 2001

Modulated components of a speech signal are frequently used for speech coding, speech recognition, and speech synthesis. Time-frequency representation (TFR) reveals some information about instantaneous frequency, instantaneous bandwidth and boundary of each component of the considering speech signal. In many cases, the extraction of AM-FM components corresponding to instantaneous frequencies is difficult since the Fourier spectra of the components with time-varying instantaneous frequency are overlapped each other in Fourier frequency domain. In this paper, an efficient method decomposing speech signal into AM-FM components is proposed. A variable bandwidth filter is developed for the decomposition of speech signals with time-varying instantaneous frequencies. The variable bandwidth filter can extract AM-FM components of a speech signal whose TFRs are not overlapped in timefrequency domain. Also, amplitude and instantaneous frequency of the decomposed components are estimated by using Hilbert transform.

• 한국통신학회논문지
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• 제25권10B호
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• pp.1769-1776
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• 2000

In this paper a new method is proposed to identify a modulation method in the case of unknown digitally modulated input signals. The proposed identification method is implemented with an artificial neural network which is based on characteristic feature extracted from the instantaneous amplitude the instantaneous phase and the instantaneous frequency of the input signals. The proposed method was simulated with 9 type signals (ASK2, FSK2, FSK4, PSK2, PSK4, PSK8, QAM8, QAM16) in a noisy communication environment. The results show that the artificial neural network can accurately recognize all kinds of patterns.