• Journal of Ocean Engineering and Technology
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• v.25 no.2
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• pp.1-6
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• 2011

Vibration-based Structural Health Monitoring (SHM) systems use field measurements of operational signals, which are distorted by noise from many sources. Reducing this noise allows a more accurate assessment of the original "clean" signal and improves analysis results. The implementation of a noise reduction methodology for the Modal Distribution Method (MDM) is reported here. The spectral subtraction method is a popular broadband noise reduction technique used in speech signal processing. Its basic principle is to subtract the magnitude of the noise from the total noisy signal in the frequency domain. The underlying assumption of the method is that noise is additive and uncorrelated with the signal. In speech signal processing, noise can be measured when there is no signal. In the MDM, however, the magnitude of the noise profile can be estimated only from the magnitude of the Power Spectral Density (PSD) at higher frequencies than the frequency range of the true signal associated with structural vibrations under the additional assumption of white noise. The implementation of the spectral subtraction method to MDM may decrease the energy of the individual mode. In this work, a modification of the spectral subtraction method is introduced that enables the conservation of the energies of individual modes. The main difference is that any (negative) bars with a height below zero after subtraction are set to the absolute value of their height. Both noise reduction methods are implemented in the MDM, and an application example is presented that demonstrates its effectiveness when used with a signal corrupted by noise.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.4
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• pp.192-197
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• 2013

Road traffic noise barriers being used to reduce the noise, but the city surroundings inhibition, ecosystem disturbance, and it is difficult to maintain. Can enhance or complement the existing noise barrier performance, so that it is necessary to develop an electronic noise-reduction system In this paper, we proposed an electronic road noise reduction devices to reduce road noise for a DSP-based signal processing and analog signal input-output controller. In order to verify the control performance, we performed noise reduction experimentation of ANC by filtered-X LMS algorithm and traffic noise signal injection. The controller is equipped with noise reduction algorithms were tested on the characteristics of directional and omnidirectional speaker.

• International Journal of Highway Engineering
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• v.15 no.6
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• pp.41-47
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• 2013

PURPOSES : The purpose of this study is about noise which is generated from roads and is consist of irregular frequency variation from low frequency to various band. The existing methods of noise reduction are sound barrier that uses insulation material and absorbing material or have applied passive technology of noise reduction by devices. The total frequency band is needed to apply active noise control. METHODS : In this study applies to the field of road traffic environment, signal processing controller and various analog signal input/output, the amplifier module is based on parallel-core embedded processor designed. DSP performs the control algorithm of the road traffic noise. Noise sources in the open space performance of evaluation were applied. In this study, controller of active signal processor was designed based on the module of audio input/output and main controller of embedded process. The controller of active signal processor operates noise reduction algorithm and performance tests of noise reduction in inside and outside environment were executed. RESULTS : The signal processing controller with OMAP-L137 parallel-core processors as the center, DSP processors in the active control operations dealt with quickly. To maximize the operation speed of an object and ARM processor is external function keys and display for functions and evaluating the performance management system was designed for the purpose of the interface. Therefore the reduction of road traffic noise has established an electronic controller-based noise reduction. CONCLUSIONS : It is shown that noise reduction is effective in the case of pour tonal sound and complex tonal sound below 500Hz by appling to Fx-LMS.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.121-128
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• 2005

On the research field for speech signal, neural network mainly uses for the category classification in speech recognition and applies to signal processing. Accordingly, this paper proposes a noise reduction system using a time-delay neural network, which implements the mapping from the space of speech signal degraded by noise to the space of clean speech signal. It is confirmed that this method is effective for speech degraded not only by white noise but also by colored noise using the noise reduction system, which restores the amplitude component of fast Fourier transform.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.103-109
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• 2014

This paper related with the CR-MMA which is possible to improving the equalization performance by applying the concept of constellation reduction in the MMA adaptive equalization alogorithm in order to reduce the intersymbol interference that is occurred in the nonlinear communication channel. In the updating process of MMA adaptive equalizer, the error signal is being obtained by using the equalizer output, and the performance will be degraded by the increase the error signal in the high order QAM constellation. But by using the constellation reduction, the high order QAM signal will be changed to the 4-QAM signal constellation and then the error signal will be obtained. By doing so, the error signal will be minimized and it is possible to improve the equalization performance in the high order QAM transmitted signal. The Computer simulation was performed in order to compare the performance of the proposed CR-MMA algorithm and original MMA algorithm in the same communication channel and noise environment. For this, the recoverd signal constellation which is the output of equalizer, residual isi and MD (Maximum Distortion) learning curve which is represents the convergence performance and SER which is represents the roburstness of noise were used. As a result of simulation, the CR-MMA has more superior to the MMA. And it was confirmed that the CR-MMA has roburstness to the noise in the SER performance.

• Journal of the Korean Institute of Telematics and Electronics
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• v.12 no.3
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• pp.30-36
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• 1975

Distortions are analyzed and compared for two TDM channel expansion methods- periodic sample skipping and sampling frequency reduction. Signal is assumed to be stationary random signal with zero.mean. Channel noise and interference are not considered in the analysis. For speech signal, it is shown that the periodic sample skipping method could be a better choice under practical design constraints.

• 전기의세계
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• v.22 no.4
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• pp.25-29
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• 1973

The computation of transmittances between arbitrary input and output nodes is of particular interest in the signal flow graph theory imput. The signal flow matrix [T] can be defined by [X]=-[T][X] where [X] and [Y] are input nose and output node matrices, respectively. In this paper, the followings are discussed; 1) Reduction of nodes by reforming the signal flow matrix., 2) Solution of input-output relationships by means of Gauss-Jordan reduction method, 3) Extension of the above method to the matrix signal flow graph.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2247-2252
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• 2009

Since the dimensions of MEMS gyroscope are very small compared to those of conventional gyroscope, MEMS gyroscope should be able to measure charge of pico-coulomb caused by very small change of electrodes gap. However, feed-through signal from driving electrodes to the sensing electrodes due to the electromagnetic coupling is much greater than the sensing signal, which degrades the sensitivity of MEMS gyroscope. This paper introduces the feed-through noise canceling technique using dummy port and confirms the feasibility of feed-through noise canceling experimentally. Experimental results shows that, when driving signal is 6 Vpp, 30 kHz, feed-through signal of vacuum packaged Si Gyroscope decreases from -53.2 dBm to -77.1 dBm by using feed-through reduction technique. Q-factor that could not be measured without noise reduction is measured to be about 2500 and resonance frequency to be 7.018 kHz.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.748-764
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• 2019

In order to deal with the filtering delay problem of least mean square adaptive filter noise reduction algorithm and music noise problem of spectral subtraction algorithm during the speech signal processing, we combine these two algorithms and propose one novel noise reduction method, showing a strong performance on par or even better than state of the art methods. We first use the least mean square algorithm to reduce the average intensity of noise, and then add spectral subtraction algorithm to reduce remaining noise again. Experiments prove that using the spectral subtraction again after the least mean square adaptive filter algorithm overcomes shortcomings which come from the former two algorithms. Also the novel method increases the signal-to-noise ratio of original speech data and improves the final noise reduction performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.201-204
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• 2011

For efficient noise reduction in a Fourier transform ion cyclotron resonance (FT-ICR) mass spectrum, a new algorithm was proposed. The suggested algorithm reduces white and electrical noise, and it improves signal-to-noise ratio. This algorithm has been optimized to reduce the noise more efficiently using the traces of signal level. The algorithm has been efficiently combined with derivative window to improve the resolution as well S/N. Time domain data was corrected for DC voltage interference. $t^n$ window was applied in time domain data to improved the resolution. However, $t^n$ window can improve the signal resolution, it will also increase the noise level in frequency domain. Therefore, newly developed noise reduction algorithm will be applied to make a balance between resolving power and S/N ratio for magnitude mode. The trace algorithm can determine the current data point with several data points (mean, past data, calculated past data). In the current calculations, we assumed data points with S/N ratio more than 3 were considered as signal data points. After the windowing and noise reduction, both resolution and signal-to-noise ratio were improved. This algorithm is applicable more efficiently to frequency dependent noise and large size data.