• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.1
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• pp.13-26
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• 2011

In order to explain the U-shaped pattern of autocorrelations of stock returns i.e., autocorrelations starting around 0 for short-term horizons and becoming negative and then moving toward 0 for long-term horizons, researchers suggested the use of a state-space model consisting of an I(1) permanent component and an AR(1) stationary component, where the two components are assumed to be independent. They concluded that auto-regression coefficients derived from the state-space model follow a U-shape pattern and thus there is mean-reversion in stock prices. In this paper, we show that only negative autocorrelations are feasible under the assumption that the permanent component and the stationary component are independent in the state-space model. When the two components are allowed to be correlated in the state-space model, we show that the sign of the auto-regression coefficients is not restricted as negative. Monthly return data for all NYSE stocks for the period from 1926 to 2007 support the state-space model with correlated noise processes. However, the auto-regression coefficients of the ARIMA process, equivalent to the state-space model with correlated noise processes, do not follow a U-shaped pattern, but are always positive.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.9-12
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• 1991

The correlation search method yields velocity information by tracking scatter patterns between medical image frames. The displacement vector between a target region and the best correlated search region indicates the magnitude and direction of the inter-frame motion of that particular region. However, if the noise sources in the target region and the search region are correlated Gaussian, then the cross-correlation technique fails to work well because it estimates the cross-correlation of both signals and noises. In this paper we develop a new correlation search method which seeks the best correlated third-order statistics between a target and the search region to suppress the effect of correlated Gaussian noise sources. Our new method yields better estimations of velocity than the conventional cross-correlation method.

• Progress in Superconductivity
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• v.4 no.2
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• pp.114-120
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• 2003

We employed a method eliminating a temporally partial principal component (PC) of multichannel-recorded neuromagnetic fields for excluding spatially correlated noises from event-evoked signals. The noises in magnetoencephalography (MEG) are considered to be mainly spontaneous neuromagnetic fields which are spatially correlated. In conventional MEG experiments, the amplitude of the spontaneous neuromagnetic field is much lager than that of the evoked signal and the synchronized characteristics of the correlated rhythmic noise makes it possible for us to extract the correlation noises from the evoked signal by means of the general PC analysis. However, the whole-time PC of the fields still contains a little projection component of the evoked signal and the elimination of the PC results in the distortion of the evoked signal. Especially, the distortion will not be negligible when the amplitude of the evoked signal is relatively large or when the evoked signals have a spatially-asymmetrical distribution which does not cancel out the corresponding elements of the covariance matrix. In the period of prestimulus, there are only the spontaneous fields and we can find the pure noise PC that is not including the evoked signal. Besides that, we propose a method, called the extended temporal decorrelation method (ETDM), to suppress the distortion of the noise PC from remanent evoked signal components. In this study, we applied the Partial Principal component elimination method (PPCE) and ETDM to simulated signals and the auditory evoked signals that had been obtained with our homemade 37-channel magnetometer-based SQUID system. We demonstrate here that PPCE and ETDM reduce the number of epochs required in averaging to about half of that required in conventional averaging.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.102-105
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• 2002

A noise reduction technique to reduce background noise in corrupted voice is proposed. The proposed method is based on linear prediction and takes advantages of periodicity of voiced speech. A voiced sound is regarded as a periodic stationary signal in short time interval. Therefore, the current voice signal is correlated with the voice signal delayed by a pitch period. A linear predictor can estimate only the current signal correlated with the delayed signal. Therefore, the enhanced voice can be obtained as output of the linear predictor. Simulation results show that the proposed method is able to reduce the background noise.

• ETRI Journal
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• v.36 no.4
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• pp.599-608
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• 2014

This paper studies a parallel relay network where the relays employ an amplify-and-forward (AF) relaying scheme and are subjected to individual power constraints. We consider correlated effective relay noise arising from practical scenarios when the relays are exposed to common interferers. Assuming that the noise covariance and the full channel state information are available, we investigate the problem of finding the optimal AF scheme in terms of maximum end-to-end transmission rate. It is shown that the maximization problem can be equivalently transformed to a convex semi-definite program, which can be efficiently solved. Then an upper bound on the maximum achievable AF rate of this network is provided to further evaluate the performance of the optimal AF scheme. It is proved that the upper bound can be asymptotically achieved in two special regimes when the transmit power of the source node or the relays is sufficiently large. Finally, both theoretical and numerical results are given to show that, on average, noise correlation is beneficial to the transmission rate - whether the relays know the noise covariance matrix or not.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.06a
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• pp.7-8
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• 2009

In the presence of infrared light, a CMOS Readout IC (ROIC) for a microbolometer typed infrared sensor detects the voltage or current that is caused by the changing in resistance in the bolometer sensor. A serious problem in designing the ROIC is how the value of the bolometer and reference resistors vary because of variations in manufacturing process. Since different pixel have different, resistance values, sensor operations must contend with fixed pattern noise (FPN) problems. In this paper, we propose a novel technique to compensate for the fluctuation in reference resistance by tiling into account the process variation. By using constant current source basing and correlated double sampling, we solved FPN.

• Economic and Environmental Geology
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• v.38 no.2 s.171
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• pp.155-163
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• 2005

For an unbiased TF (Tansfer Function) estimations we investigate geomagnetic TF derived from ICHEON and YONGIN sites, employing RR (Remote Reference) and SNS (Signal Noise Separation) techniques. The Rh technique, which requires synchronized field variations recorded at a clean remote site, is a reliable method to minimize the bias of TF by uncorrelated noises in magnetic channels. Meanwhile, SNS technique based on the assumption of noise-free remote data can improve the signal-noise level by separating signal TF and noise TF, which is successfully applied to the environments with strong correlated noises. In this study, TF at YONGIN is analyzed using geomagnetic data from ICHEON site as a remote reference, which seem to have somewhat better data quality. The application of Rh technique reduces the bias of TF, which appears in single site robust estimation, and makes curves in the amplitude and phase of TF more smooth as frequency. Futhermore, in order to investigate noise source quantitatively, SNS technique is applied. The results of SNS suggest that dominant noise source seems to be located at western region of YONGIN. This noise source is considered to originate from railway system such as KTX and national subway. which passes through the west regions of YONGIN.

• Phonetics and Speech Sciences
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• v.8 no.1
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• pp.63-69
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• 2016

The aims of the present study are two-fold: 1) to explore differences on speech perception between younger and older adults according to noise conditions; and 2) to investigate which cognitive domains are correlated with speech perception. Data were acquired from 15 younger adults and 15 older adults. Sentence recognition test was conducted in four noise conditions(i.e., in-quiet, +5 dB SNR, 0 dB SNR, -5 dB SNR). All participants completed auditory and cognitive assessment. Upon controlling for hearing thresholds, the older group revealed significantly poorer performance compared to the younger adults only under the high noise condition at -5 dB SNR. For older group, performance on Seoul Verbal Learning Test(immediate recall) was significantly correlated with speech perception performance, upon controlling for hearing thresholds. In older adults, working memory and verbal short-term memory are the best predictors of speech-in-noise perception. The current study suggests that consideration of cognitive function for older adults in speech perception assessment is necessary due to its adverse effect on speech perception under background noise.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.59-64
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• 2005

To achieve a goal of minimum output power, the beamformer tends to cancel the desired signal if there exists correlated interference sources such as multipaths of the desired signal. In this paper, we propose a new method which overcomes the signal cancellation problem for correlated interferences. Instead of decorrelating the correlated interferences, the proposed bramformer regards them as replicas of the desired signal and coherently combines them with desired signal. This method uses an eigenvector constraint that suppresses a noise and uncorrelated interferences but keeps the desired signal and correlated interferences. Indisputably, the beamformer does not require any preliminary information on correlated interferences. Simulation results show that the proposed beamformer overcomes the signal cancellation problem and improves signal-to-noise ratio (SNR) of the array output when the correlated interferences exist.

• International Journal of Automotive Technology
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• v.8 no.1
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• pp.75-82
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• 2007

This paper presents practical work on the reduction of gear whine noise. In order to identify the source of the gear whine noise, transfer paths are searched and analyzed by operational deflection shape analysis and experimental modal analysis. It was found that gear whine noise has an air-borne noise path instead of structure-borne noise path. The main sources of air-borne noise were the two global modes caused by the resonance of an axle system. These modes created a vibro-acoustic noise problem. Vibro-acoustic noise can be reduced by controlling the vibration of the noise source. The vibration of noise source is controlled by the modification of structure to avoid the resonance or to reduce the excitation force. In the study, the excitation force of the axle system is attenuated by changing the tooth profile of the hypoid gear. The modification of the tooth profile yields a reduction of transmission error, which is correlated to the gear whine noise. Finally, whine noise is reduced by 10 dBA.