• Journal of the Korean Society of Safety
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• v.12 no.4
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• pp.3-8
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• 1997

This paper shows a performance estimation of windowing a single tone with added Gaussian noise and uniform noise. Signal-to-noise ratio can be determined by the ratio of the output noisy signal variance to the input noisy signal variance of a window. Standard deviation of noise is reduced by windowing Signal-to-noise ratio of the noisy signal is reduced by the windowing operation. Thus, performance of window function can be determined by this filtering operation that improved the signal-to-noise ratio.

• Nuclear Engineering and Technology
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• v.46 no.6
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• pp.883-888
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• 2014

This work presents the influence of noise originating from the tube itself on the detectability and sizing accuracy for laboratory-induced outer diameter axial cracks in nuclear steam generator tubes. The variations of signal amplitude and phase angle of the same cracks were analyzed when increasing the signal-to-noise ratio of the tube itself from 9 to 18. It was experimentally verified that the detectability for small cracks was enhanced by increasing the signal-to-noise ratio. The phase angle also rotated to a value representing the actual position and depth of a crack when increasing the signal-to-noise ratio.

• 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 Magnetics
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• v.19 no.2
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• pp.185-191
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• 2014

In this study we evaluated that flow rate changes affect the (time of flight) TOF image and contrast-enhanced (CE) in a three-dimensional TOF angiography. We used a 3.0T MR System, a nonpulsatile flow rate model. Saline was used as a fluid injected at a flow rate of 11.4 cm/sec by auto injector. The fluid signal strength, phantom body signal strength and background signal strength were measured at 1, 5, 10, 15, 20 and 25-th cross-section in the experienced images and then they were used to determine signal-to-noise ratio and contrast-to-noise ratio. The inlet, middle and outlet length were measured using coronal images obtained through the maximum intensity projection method. As a result, the length of inner cavity was 2.66 mm with no difference among the inlet, middle and outlet length. We also could know that the magnification rate is 49-55.6% in inlet part, 49-59% in middle part and 49-59% in outlet part, and so the image is generally larger than in the actual measurement. Signal-to-noise ratio and contrast-to-noise ratio were negatively correlated with the fluid velocity and so we could see that signal-to-noise ratio and contrast-to-noise ratio are reduced by faster fluid velocity. Signal-to-noise ratio was 42.2-52.5 in 5-25th section and contrast-to-noise ratio was from 34.0-46.1 also not different, but there was a difference in the 1st section. The smallest 3D TOF MRA measure was $2.51{\pm}0.12mm$ with a flow velocity of 40 cm/s. Consequently, 3D TOF MRA tests show that the faster fluid velocity decreases the signal-to-noise ratio and contrast-to-noise ratio, and basically it can be determined that 3D TOF MRA and 3D CE MRA are displayed larger than in the actual measurement.

• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.334-337
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• 2005

The speech intelligibility is one of the most important factors in communication system. The speech intelligibility is related with speech to noise ratio. To enhance the speech to noise ratio, background noise reduction techniques are being developed. As a part of solution to noise reduction, this paper introduces directional microphone using beamforming method and speech filtering method. The directional microphone narrows the spatial range of processing signal into the direction of the target speech signal. The noise signal located in the same direction with speech still remains in the processing signal. To sort this mixed signal into speech and noise, as a following step, a speech-filtering method is applied to pick up only the speech signal from the processed signal. The speech filtering method is based on the characteristics of speech signal itself. The combined directional microphone and speech filtering method gives enhanced performance to speech intelligibility in communication system.

• 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.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.28A no.1
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• pp.1-7
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• 1991

Degradation of communication quality is due to transmission error rather than quantization noise when DPCM signal is transmitted over a heavily noise channel. The communication quality can be improved by employing an error correcting code to the DPCM signal transmission over such a channel. We considered both quantization noise and transmission error simultaneously in evaluating the signal to noise ratio. To efficiently improve the signal to noise ratio, we analyze the unequal symbol error probability of convolutional code, and encoded to more protect significant symbols from channel errors than least ones, so that the signal to noise ratio is improved. We derived related formulas and also made computer simulations.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.1
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• pp.54-62
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• 1999

In this paper, we investigated the signal-to-noise ratio improvement in a differential detector, which is a function of the optical noise coupling ratio and the differential gain ratio. A differential detector consists of two photodiodes and a differential amplifier. The differential detector reduced the noise component and improved the signal-to-noise ratio by about 20 dB when the differential gain ratio equals to the optical noise coupling ratio. The differential detector is very effective in removing the environmental optical noise or interference from an adjacent optical channel. This method is also effective when the noise wavelength is similar to the signal.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.20-33
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• 2015

Spectrum sensing is a key component of cognitive radio. The prediction of the primary user status in a low signal-to-noise ratio is an important factor in spectrum sensing. However, because of noise uncertainty, secondary users have difficulty distinguishing between the primary signal and an unauthorized signal when an unauthorized user exists in a cognitive radio network. To resolve the sensitivity to the noise uncertainty problem, we propose an entropy-based spectrum sensing scheme to detect the primary signal accurately in the presence of an unauthorized signal. The proposed spectrum sensing uses the conditional entropy between the primary signal and the unauthorized signal. The ability to detect the primary signal is thus robust against noise uncertainty, which leads to superior sensing performance in a low signal-to-noise ratio. Simulation results show that the proposed spectrum sensing scheme outperforms the conventional entropy-based spectrum sensing schemes in terms of the primary user detection probability.