• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.202-207
• /
• 2002

EOC (Electro-Optical Camera) of KOMPSAT-1 (Korea Multi-Purpose SATellite) has been producing land imageries of the world since January 2000. After image data are acquired by EOC, they are transmitted from satellite to ground via X-band RF signal. Then, EOC image data are generated and pass through radiometric and geometric corrections to generate standard products of EOC images. After radiometric correction on EOC image data, Modulation Transfer Function (MTF) compensation is applicable on EOC images with user's request for better image quality. MTF compensation is concerned with filtering EOC images to minimize the effect of degradations. For Image Receiving and Processing System (IRPE) at KOMPSAT Ground Station (KGS), Wiener filter is used in MTF compensation for EOC images. If the Pointing Spread Function (PSF) of EOC system is known, signal-to-noise power spectra ratio is the only factor in the determination of Wiener filter. In this paper, MTF compensation in IRPE at KGS is introduced and MTF compensated EOC 1R images are generated using Wiener filters with various signal-to-noise power spectra ratios. MTF compensated EOC 1R images are correlated with EOC 1R images for observing linearities between them. As a result, the effect of signal-to-noise power spectra ratio is shown on MTF compensated EOC 1R images.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.05a
• /
• pp.495-498
• /
• 2004

In the sound insulation measurements, the influence of background (extraneous) noise is often serious problem and how to reduce its effect and to improve the signal-to-noise(S/N) ratio is an important theme. As the background noise, such extraneous noises as road traffic noise and machine noise often disturb the measurement. In laboratory measurements on specimens with high sound insulation performances, even the internal noise of the measurement system can become a problem. To improve the signal-to-noise ratio and to improve the measurement accuracy, various kinds of digital signal processing techniques can be applied. In this paper, four kinds of digital signal processing techniques are applied and their effectiveness is examined by a simple sound insulation measurement.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.11a
• /
• pp.441-444
• /
• 2004

In the sound insulation measurements, the influence of background (extraneous) noise is often serious problem and how to reduce its effect and to improve the signal-to-noise(S/N) ratio is an important theme. As the background noise, such extraneous noises as road traffic noise and machine noise often disturb the measurement. In laboratory measurements on specimens with high sound insulation performances, even the internal noise of the measurement system can become a problem. To improve the signal-to-noise ratio and to improve the measurement accuracy, various kinds of digital signal processing techniques can be applied. In this paper, four kinds of digital signal processing techniques are applied and their effectiveness is examined through field measurements.

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

• Journal of Korea Multimedia Society
• /
• v.23 no.3
• /
• pp.402-411
• /
• 2020

Power line noise in electrocardiogram signals makes it difficult to diagnose cardiovascular disease. ECG signals without power line noise are needed to increase the accuracy of diagnosis. In this paper, it is proposed DNN(Deep Neural Network) model to remove the power line noise in ECG. The proposed model is learned with noisy ECG, and clean ECG. Performance of the proposed model were performed in various environments(varying amplitude, frequency change, real-time amplitude change). The evaluation used signal-to-noise ratio and root mean square error (RMSE). The difference in evaluation metrics between the noisy ECG signals and the de-noising ECG signals can demonstrate effectiveness as the de-noising model. The proposed DNN model learning result was a decrease in RMSE 0.0224dB and a increase in signal-to-noise ratio 1.048dB. The results performed in various environments showed a decrease in RMSE 1.7672dB and a increase in signal-to-noise ratio 15.1879dB in amplitude changes, a decrease in RMSE 0.0823dB and a increase in signal-to-noise ratio 4.9287dB in frequency changes. Finally, in real-time amplitude changes, RMSE was decreased 0.3886dB and signal-to-noise ratio was increased 11.4536dB. Thus, it was shown that the proposed DNN model can de-noise power line noise in ECG.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.8
• /
• pp.1332-1338
• /
• 1997

In the case of the transfer function for the secondary path is dependent on time, the on-line method which can model it is continuously must be applied to the active noise control technique. And the adaptive random noise technique among the on-line methods is effective in the narrow-band control. In this method, the signal to noise ratio between random noise for modeling and primary noise is low. Therefore, the estimations of transfer function will be prone to inaccuracies and the convergence time will be too long. Such imperfections will have an influence upon the performance of an active noise controller. In this study, t enhance the signal to noise ratio, the on-line method that is combined the conventional adaptive random noise technique and the adaptive line enhancer, is proposed. By using proposed on-line method, a rigorous system identification and control of primary noise have been implemented.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.7C
• /
• pp.413-420
• /
• 2011

This paper proposes a new adaptive algorithm to cancel the acoustic feedback and noise signals in the binaural hearing aids. The convergence performances of the proposed algorithm are improved by updating coefficients of the feedback canceller after the speech signal is cancelled from the residual signal with dual microphones. The feedback canceller firstly cancels the feedback signal from the microphone signal, and then the noise canceller reduces the noise by the beamforming method. To assure that binaural hearing aids converge stably, the left-sided hearing aid only is converged firstly, next the right-sided hearing aid only is converged. To verify performances of the proposed algorithm, simulations were carried out for a speech. As the results of simulations, it was proved that we can advance 14.43dB SFR(Signal to Feedback Ratio) on the average for the feedback canceller, 10.19dB SNR(Signal to Noise Ratio) improvement on the average for the noise canceller, in case that this algorithm is used.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.13 no.5
• /
• pp.24-29
• /
• 1976

In the phase locked AM signal detection, phase locked loop is used to extract a synchronous carrier from an input AM signal. Under the assumption that input noise is white Gaussian and free-running frequency of voltage controlled oscillator is the same that of an input carrier, operational behaviours of phase locked loop is analyzed and signal to noise ratio of the detection is derived quentitatively. The results show that the phase locked AM signal detection method offers a higher degree of noise mmunity than conventional AM signal detections.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.285-288
• /
• 2008

In ubiquitous computing environment the biological signal ECG (Electrocardiogram signal) is usually recorded with noise components. Adaptive interference (or noise) canceller do adaptive filtering of the noise reference input to maximally match and subtract out noise or interference from the primary (signal plus noise) input thereby adaptively eliminate unwanted interference from the ECG signal. Measured Stress ECG (or exercise ECG signal) signal have three major noisy component like baseline wander noise, motion artifact noise and EMG (Electro-mayo-cardiogram) noise. These noises are not only distorted signal but also root of incorrect diagnosis while ECG data are analyzed. Motion artifact and EMG noises behave like wide band spectrum signals, and they considerably do overlapping with the ECG spectrum. Here the multidimensional adaptive method used for filtering which is more effective to improve signal to noise ratio.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.10
• /
• pp.168-174
• /
• 2015

In this paper, we analyze the performance of cooperative communication techniques on an underwater channel. By analyzing the BER performance of cooperative transmission protocol and combining types ERC, FRC, SNRC and ESNRC on underwater channel, through the result, we can choose an a proper cooperative technique for an underwater channel. The analysis of BER performance is achieved by a computer simulation.