• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.181-186
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• 2011

In this paper, we propose the Noise Cancel DTW that to use a kind of feature compensation. This method is not to use estimated noise but we use real life environment noise data for Voice Recognition. And we applied this contaminated data for recognition reference model that suitable for noise environment. NCDTW is combined with surround noise when generating reference patten. We improved voice recognition rate at mobile environment to use NCDTW.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2879-2881
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• 1999

This paper presents the adaptive Active Noise Control(ANC) system using the Neuro-Fuzzy controller. In general, the character of noise is time-varing and nonlinear Thus controller must have the adaptivness so that applied in Active Noise Control system to cancel the noise. This paper propose the Neuro-Fuzzy controller trained with back-propagation teaming algorithm to optimize the parameters of controller The objects of this paper are cancel the noise, extract the original(speech) signal polluted by noise and design the Neuro-Fuzzy controller.

• Journal of Korea Water Resources Association
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• v.42 no.4
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• pp.355-363
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• 2009

The purpose of this paper is to investigate the influence of noise on chaotic time series. We used two time series of Lorenz system and of Great Salt Lake's volume data which are well known as chaotic systems. This study investigated the attractors, correlation dimensions, and Close Returns Plots and Close Returns Histograms of two time series to investigate the influence of noise as increasing noise level. We performed Chi-square test to the relative frequency of Close Returns Histogram from Close Returns Plot for the investigation of stochastic process of chaotic time series as increasing noise level of time series. As the results, two time series were changed from chaotic to stochastic series as noise level is increased. Finally, we analyzed the effect of noise cancellation by using Simple Moving Average method. The results of applications of Simple Moving Average method to Lorenz and GSL time series showed that we could effectively cancel the noise. Then we could confirm the applicability of Simple Moving Average method to cancel the noise for the hydrologic time series having chaotic characteristics.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.500-503
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• 2002

Biomedical signals are ubiquitously contaminated and degraded by background noise which span nearly all frequency bandwidths. This paper proposes the MADF (multiplication free adaptive digital filter) algorithm to cancel the noise. And the convergence characteristics of the algorithm is analyzed. In the experimental results, the MADF algorithm has the advantage in which has superior to a condition of low-frequency and slow data speed. This application gives an important significance in ensuring the objectivity of clinical information and in promoting the representation and the disease diagnosis.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.93-102
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• 1998

In noisy environments, human speech productions are influenced by noises(Lombard effect), and speech signals are contaminated. These distortions dramatically reduce the performance of speech recognition systems. This paper proposes a method of the Lombard effect compensation and noise suppression in order to improve speech recognition performance in noise environments. To estimate the intensity of the Lombard effect which is a nonlinear distortion depending on the ambient noise levels, speakers, and phonetic units, we formulate the measure of the Lombard effect level based on the acoustic speech signal, and the measure is used to compensate the Lombard effect. The distortions of speech under noisy environments are cancelled out as follows. First, spectral subtraction and band-pass filtering are used to cancel out noise. Second, energy nomalization is proposed to cancel out the variation of vocal intensity by the Lombard effect. Finally, the Lombard effect level controls the transform which converts Lombard speech cepstrum to clean speech cepstrum. The proposed method was validated on 50 korean word recognition. Average recognition rates were 82.6%, 95.7%, 97.6% with the proposed method, while 46.3%, 75.5%, 87.4% without any compensation at SNR 0, 10, 20 dB, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.550-553
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• 1993

Methods of Alternating Noise Canceling were previously developed for the optical instrumentation;one using a dual photo sensor and another using a single photo sensor that could cancel normal mode noise on a transmission line, even if the noise was of equal status noise. But the methods could not remove noise on sensor line. This paper discusses a new method of using a photo sensor with a resistance sensordummy, effectively canceling equal status normal mode noise not only on a sensor line but also on a transmission line of an optical instrumentation. The accuracy of this method has been verified by experiments using sinusoidal wave as an equal status noise on a sensor line and/or rectangular wave as an equal status wide band noise on a transmission line respectively.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1326-1335
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• 2019

Common mode (CM) chokes are a crucial part in EMI filters for mitigating the electromagnetic interference (EMI) of switched-mode power supplies (SMPS) and for meeting electromagnetic compatibility standards. However, the parasitic capacitances of a CM choke deteriorate its high frequency filtering performance, which results in increases in the design cycle and cost of EMI filters. Therefore, this paper introduces a negative capacitance generated by a negative impedance converter (NIC) to cancel the influence of equivalent parallel capacitance (EPC). In this paper, based on a CM choke equivalent circuit, the EPCs of CM choke windings are accurately calculated by measuring their impedance. The negative capacitance is designed quantitatively and the EPC cancellation mechanisms are analyzed. The impedance of the CM choke in parallel with negative capacitances is tested and compared with the original CM choke using an impedance analyzer. Moreover, a CL type CM filter is added to a fabricated NIC prototype, and the insertion loss of the prototype is measured to verify the cancellation effect. The prototype is applied to a power converter to test the CM conducted noise. Both small signal and EMI measurement results show that the proposed technique can effectively cancel the EPCs and improve the CM filter's high frequency filtering performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.175-179
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• 2011

In this paper, we propose the MA(Model Adaption) HMM that to use speech enhancement and feature compensation. Normally voice reference data is not consider for real noise data. This method is not to use estimated noise but we use real life environment noise data. And we applied this contaminated data for recognition reference model that suitable for noise environment. MAHMM is combined with surround noise when generating reference patten. We improved voice recognition rate at mobile environment to use MAHMM.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.12
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• pp.106-113
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• 1997

While driving, the low frequency interior noise below 200Hz causes the main component that irritates the auditory acoustic sense. But these passive control methods bring out increment in cost and weight of the vehicle and result in low efficiency. Recently, various ANC(Active Noise Control) methos to suppress the low frequency noise began to launch into application. In this study, we implemented the active noise control system for passenger vehicle to cancel the engine booming noise using DSP-based control unit, 4 micorphones, and 2 speakers. We used MEFX-LMS (Multiple Error Filtered X-Least Mean Square) algorithm since it can be easily implemented in real time. Also, MEFX-RLS algorithm was taken to enhance the suppression of the harmonic components of the engine booming noise inspite of its computational complexity. The performance of two adaptive algorithms were analyzed with experimental resutls.

• Journal of Biomedical Engineering Research
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• v.34 no.4
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• pp.204-211
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• 2013

In this paper, an algorithm for suppressing acoustic noises contained in stethoscope sound is proposed and implemented in real-time using an embedded DSP system. Sound collected by stethoscope is down-sampled and band-pass filtered, and later an NLMS adaptive filter is used to cancel the acoustic noise induced from external noise sources. Also, the unpredictable impulsive noises due to fabric friction and instantaneous tapping are detected using the SD-ROM algorithm, and suppressed using an algorithm approximating the morphology filter. The proposed algorithm was tested using signals collected with a digital stethoscope mockup, and implemented on an ARM920T-based DSP system.