• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.167-173
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• 2005

This paper presents an autocorrelation test that is applicable to dynamic panel data models with serially correlated errors. The residual-based GMM t-test is a significance test that is applied after estimating a dynamic model by using the instrumental variable(IV) method and is directly applicable to any other consistently estimated residuals. Monte Carlo simulations show that the t-test has considerably more power than the $m_2$ test or the Sargan test under both forms of serial correlation (i.e., AR(1) and MA(1)).

• Journal of the Korean Statistical Society
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• v.34 no.4
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• pp.367-375
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• 2005

This paper presents an autocorrelation test that is applicable to dynamic panel data models with serially correlated errors. The residual-based GMM t-test is a significance test that is applied after estimating a dynamic model by using the instrumental variable (IV) method and is directly applicable to any other consistently estimated residuals. Monte Carlo simulations show that the t-test has considerably more power than the $m_2$ test or the Sargan test under both forms of serial correlation (i.e., AR(1) and MA(1)).

• The Journal of the Acoustical Society of Korea
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• v.20 no.2E
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• pp.25-29
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• 2001

In this paper, we propose a new method for selecting the threshold on wavelet packet denoising. In selecting threshold, the method using median is not efficient. Because this method can not recover unvoiced signal corrupted by noise. So we partition a speech signal corrupted by noise into the pure noise section and voiced section using autocorrelation and entropy. The autocorrelation and entropy can reflect disorder of noise. The new method yields more improved denoising effect. Especially unvoiced signal is very nicely reconstructed, and SNR is improved.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.285-288
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• 2001

In the speech analysis, to estimate formant center frequencies exactly is very important. If we know formant frequencies, we can expect which pronunciation is uttered. Generally, the magnitude of first formant frequency in voiced speech is 10dB more than other formant frequency. So, the shape of voice signal in time domain is affected by mainly first formant. Therefore we can get first formant frequency roughly by using ZCR(Zero Cross Rate). In this paper, we proposed the improvement method to get first formant frequency by using ZCR. We did autocorrelation before getting ZCR. This procedure makes voice signal smooth so, first formant in voice signal is emphasized. As a result of this method, we got more exact ZCR and first formant frequency. Conventional method of formant estimate is done in frequency domain but proposed method is done in time domain. So, this is very simple.

• Industrial Engineering and Management Systems
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• v.8 no.4
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• pp.247-256
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• 2009

In mass production industries such as steel making that have large equipment, sudden stops of production process due to machine failure can cause severe problems. To prevent such situations, machine diagnosis techniques play important roles. Many methods have been developed focusing on this subject. In this paper, we propose a method for the early detection of the failure on rotating machine, which is the most common theme in the machine failure detection field. A simplified method of calculating autocorrelation function is introduced and is utilized for ARMA model identification. Furthermore, an absolute deterioration factor such as Bicoherence is introduced. Machine diagnosis can be executed by this simplified calculation method of system parameter distance with weight. Proposed method proved to be a practical index for machine diagnosis by numerical examples.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.201-202
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• 2006

To analyze the dynamic characteristics of the bundle drawing process, we employed a Random Phase Spectrum method to generate stochastic test signals that had a given autocorrelation function. And the spectra of the dynamics of the process outputs were obtained, based on the dynamic model of the bundle drawing process. Results showed that the RPS method was very effective to generate stochastic signals that had an exponential function form. The drawing process had the traits that there existed a special frequency range, incurring the process resonance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.424-429
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• 2009

This paper suggests an autocorrelation function (AF) based carrier frequency offset (CFO) estimator based on a training sequence in flat fading channels. The proposed CFO estimator has the reduced computational burdens in the calculation of the AF when compared to AF-based conventional frequency estimators. The simulation results show that the proposed estimator achieves a better performance than the existing estimators. Furthermore, the performance of the proposed method has been observed to lie close to the Cramer-Rao lower bound (CRLB).

• Journal of Astronomy and Space Sciences
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• v.19 no.4
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• pp.327-340
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• 2002

In this paper, we performed the design study of a wide-band digital autocorrelation spectrometer for the observation study of an extra-galaxy's spectral lines and the survey research of the special radio sources in field of the radio astronomy observational research. The autocorrelation spectrometer designed in this paper can be used to their spectrometer of any system because this spectrometer has a wide dynamic power and frequency range properties. In this system we use the aliasing sampling method to minimize the band loss. For the output signal of the correlator we can increase the signal processing speed using by a special DSP chip, the integration and the FFT using hardware, so this spectrometer can support the newest developed technique for the radio astronomy observation so called “On the fly” method.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1985.10a
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• pp.179-181
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• 1985

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.529-532
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• 2002

This research treated development of real time pitch tracer for training of musical tune of speech signal and pre-processing and post-processing technics were proposed to get higher accuracy in extraction of pitch. Autocorrelation Function was used to get pitch frequency from 64Hz to 980Hz in real time. Half Rectifier method and Envelop extraction method as a pre-processing was used to get higher accuracy in pitch detection, and improved results were obtained on noised speech signal. Post-processing method using periodicity of Autocorrelation was proposed to get higher accuracy in the high frequency region.