• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.10
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• pp.35-41
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• 1993

In this paper, a new speech enhancement method for speech signal corrupted by environmental noise is proposed. Two signals are obtained from the microphone and from the accelerometer attached to the neck, respectively. Since two signals are generated from same source signal, both signals are closely correlated. And environmental noise has no effect on the accelerometer signal. The speech enhancement system identifies the optimum linear system between two signals on the basis of the dependence between the signals. The enhanced speech can be obtained by filtering the noise-free accelerometer signal. Since the characteristcs of the speech signal and environmental noise are changing with time, adaptive filtering system has to be used for characterizing the time-varing system. Simulation results show 7dB enhancement with 0dB speech signal level relative to the white noise.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.335-336
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• 2000

A psychoacoustic model based noise shaping method is proposed, where noise's presence with a host signal will not be perceptually noticeable. The derivation of imperceptible noise levels from the masking thresholds of the signal involves a deconvolution associated with the spreading function in the psychoacoustic model, which results in an ill-conditioned problem. In this paper, the problem is formulated as a constrained optimization, and it is demonstrated that the solution provides noise shaping where the noise excitation level conforms to the masking thresholds of the signal.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.12
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• pp.1287-1294
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• 2004

Hub bearings not only sustain the body of a cat, but permit wheels to rotate freely. Excessive radial or axial load and many other reasons can cause defects to be created and grown in each component. Therefore, nitration and noise from unwanted defects in outer-race, inner-race or ball elements of a Hub bearing are what we want to detect as early as possible. How early we can detect the faults has to do with how the detection algorithm finds the fault information from measured signal. Fortunately, the bearing signal has Periodic impulse train. This information allows us to find the faults regardless how much noise contaminates the signal. This paper shows the basic signal processing idea and experimental results that demonstrate how good the method is.

• Transactions of the Society of Information Storage Systems
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• v.1 no.1
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• pp.48-52
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• 2005

The research topic of super-RENS technology is shifting from the signal intensity (CNR; Carrier to Noise Ratio) to the signal uniformity (Jitter or bER). To achieve an uniform signal characteristics, it is important to reduce signal fluctuation in a super-RENS disc. In this study, we investigated the relation between signal fluctuation and low frequency noise (LFN), and analyzed LFN increase in recording and readout processes. It was found that signal fluctuation had a close relationship with the LFN. Also, it was found that the recorded mark shape such a bubble type and high readout power increased the LFN in recording and readout process of a super-RENS disc. So, using non-bubble type recording material and low super-resolution readout material, we markedly improved the LFN in a super-RENS disc.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.1
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• pp.51-57
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• 2010

This study was to analyze the difference in pilot error by using the Signal Detection Theory. The task was to detect the targeted aircraft(signal) which is different shape from many other aircraft(noise). From the two experiments, we differentiated the task difficulty followed by change in noise stimuli. Experiment 1 was to search the signal stimuli(fighter plane) while the noise stimuli(cargo plane) were increasing. The results from the Experiment 1 showed the tendency to decrease the hit rate by increasing the number of noise stimuli. However, the false alarm rate was not increased. The sensitivity(d') showed quite high. In Experiment 2, a disturbance stimulus(helicopter) was added to noise stimuli. The result was generally similar to those of Experiment 1. However, the hit rate was lower than that of Experiment 1.

• Journal of information and communication convergence engineering
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• v.14 no.4
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• pp.268-271
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• 2016

An efficient inductive switching noise suppression technique for mixed-signal integrated circuits (ICs) using standard CMOS digital technology is proposed. The proposed design technique uses a parallel RC circuit, which provides a damping path for the switching noise. The proposed design technique is used for designing a mixed-signal circuit composed of a ring oscillator, a digital output buffer, and an analog noise sensor node for $0.13-{\mu}m$ CMOS digital IC technology. Simulation results show a 47% reduction in the on-chip inductive switching noise coupling from the noisy digital to the analog blocks in the same substrate without an additional propagation delay. The increased power consumption due to the damping resistor is only 67% of that of the conventional source damping technique. This design can be widely used for any kind of analog and high frequency digital mixed-signal circuits in CMOS technology

• Journal of Sensor Science and Technology
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• v.23 no.1
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• pp.1-6
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• 2014

In many medical image devices, dc noise often prevents normal diagnosis. In wireless capsule endoscopy systems, multipath fading through indoor wireless links induces inter-symbol interference (ISI) and indoor electric devices generate impulsive noise in the received signal. Moreover, dc noise, ISI, and impulsive noise are also found in optical fiber communication that can be used in remote medical diagnosis. In this paper, a blind signal processing method based on the biased probability density functions of constant modulus error that is robust to those problems that can cause error propagation in decision feedback (DF) methods is presented. Based on this property of robustness to error propagation, a DF version of the method is proposed. In the simulation for the impulse response of optical fiber channels having slowly varying dc noise and impulsive noise, the proposed DF method yields a performance enhancement of approximately 10 dB in mean squared error over its linear counterpart.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.2
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• pp.60-65
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• 1985

A method of weighting of a staggered pulse train is presented and an improvement per-formance of the signal-to-noise ratio for each case is compared. As the result of a computer simulation, the signal-to-noise ratio for weighting of a stagger-ed pulse train is a great improvement on the case of an uniform pulse train. The signal-to-noise ratio of optimum weighting is more improved than that of binomial weighting, it is known that the signal-to-noise ratio is improved as the increasing of the number of delay line cancellers, and it is shown that the signal-to-noise ratio is improved by weighting of the MTI output pulses before the integration process.

• Journal of Broadcast Engineering
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• v.20 no.4
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• pp.568-579
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• 2015

Recently, mobile devices with touch display panel are widely used. Accuracy and reaction speed of touch signal are very important in touch devices. Therefore, we need to develop an effective algorithm to reduce touch noise quickly and accurately. This paper proposes a touch noise reduction algorithm using Kalman filtering in consideration of signal motion. First, a specific pre-emphasis processing is applied to an input signal so as to maximize the effect of Kalman filtering. In other words, a pure signal in the touch signal increases but noise in the touch signal decreases. Next, motion of the signal is detected. Motion estimation is performed only if motion is detected. If we detect motion by using the only neighborhood of the signal, we can reduce about 75% of the computation in comparison with examining the entire area. Finally, Kalman filtering using the previous state of current signal is performed. Experimental results show that the proposed algorithm suppresses touch noise sufficiently without degradation of the pure signal

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.818-827
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• 2008

In this paper, we propose a new noise estimation and reduction algorithm for stationary and nonstationary noisy environments. This approach uses an algorithm that classifies the speech and noise signal contributions in time-frequency bins. It relies on the ratio of the normalized standard deviation of the noisy power spectrum in time-frequency bins to its average. If the ratio is greater than an adaptive estimator, speech is considered to be present. The propose method uses an auto control parameter for an adaptive estimator to work well in highly nonstationary noisy environments. The auto control parameter is controlled by a linear function using a posteriori signal to noise ratio(SNR) according to the increase or the decrease of the noise level. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of much more simplicity and light computational load for estimating the stationary and nonstationary noise environments. The proposed algorithm is superior to conventional methods. To evaluate the algorithm's performance, we test it using the NOIZEUS database, and use the segment signal-to-noise ratio(SNR) and ITU-T P.835 as evaluation criteria.