• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.4-7
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• 1997

When we use Hadamard transform spectrometers (HTS), we can increase signal to noise ratio(SNR) by multiplexing which is done by masks. But if the mask has a single defective element, output-SNR decreases. In this paper the effect of a single defective element on the output-SNR is investigated. And a method of compensating for the defective mask element is presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.323-330
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• 2007

Performance indicators such as output SNR, SIR, SINR for rectangular smart antennas in CDMA basestations have been derived. Simulations have been carried out to find the rectangular smart antenna performance while varying the input SNR, number of antenna elements, and the interferers' spatial distributions. Simplified Conjugate Gradient Method was chosen as the underlying beam forming algorithm. It has been shown that the performance of a rectangular smart antenna is similar to that of the linear one having the same number of elements when the interferers are randomly distributed over the whole azimuth angle range.

• Current Optics and Photonics
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• v.6 no.6
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• pp.608-618
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• 2022

By analyzing the signal-to-noise ratio (SNR) theory of the conventional true color night vision system, we found that the output image SNR is limited by the wavelength range of the system response λ₁ and λ₂. Therefore, we built a double-channel four-band true color night vision system to expand the system response to improve the output image SNR. In the meantime, we proposed an image fusion method based on principal component analysis (PCA) and nonsubsampled shearlet transform (NSST) to obtain the true color night vision images. Through experiments, a method based on edge extraction of the targets and spatial dimension decorrelation was proposed to calculate the SNR of the obtained images and we calculated the correlation coefficient (CC) between the edge graphs of obtained and reference images. The results showed that the SNR of the images of four scenes obtained by our system were 125.0%, 145.8%, 86.0% and 51.8% higher, respectively, than that of the conventional tri-band system and CC was also higher, which demonstrated that our system can get true color images with better quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2607-2625
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• 2014

Previous studies on multiuser multiple-input multiple-output (MIMO) mostly assume a homogeneous signal-to-noise ratio (SNR), where each user has the same average SNR. However, real networks are more likely to feature heterogeneous SNRs (a random-valued average SNR). Motivated by this fact, we analyze a multiuser MIMO downlink with a zero-forcing (ZF) receiver in a heterogeneous SNR environment. A transmitter with Mantennas constructs M orthonormal beams and performs the SNR-based proportional fairness (S-PF) scheduling where data are transmitted to users each with the highest ratio of the SNR to the average SNR per beam. We develop a new analytical expression for the sum throughput of the multiuser MIMO system. Furthermore, simply modifying the expression provides the sum throughput for important special cases such as homogeneous SNR, max-rate scheduling, or high SNR. From the analysis, we obtain new insights (lemmas): i) S-PF scheduling maximizes the sum throughput in the homogeneous SNR and ii) under high SNR and a large number of users, S-PF scheduling yields the same multiuser diversity for both heterogeneous SNRs and homogeneous SNRs. Numerical simulation shows the interesting result that the sum throughput is not always proportional to M for a small number of users.

• Phonetics and Speech Sciences
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• v.3 no.1
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• pp.87-94
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• 2011

The decision directed (DD) approach is widely used to determine a priori SNR from noisy speech signals. In conventional speech enhancement systems with a DD approach, a priori SNR is estimated by using only the magnitude components and consequently follows a posteriori SNR with one frame delay. We propose a phase-dependent two-step a priori SNR estimator based on the minimum mean square error (MMSE) in the log-mel spectral domain so that we can consider both magnitude and phase information, and it can overcome the performance degradation caused by one frame delay. From the experimental results, the proposed estimator is shown to improve the output SNR of enhanced speech signals by 2.3 dB compared to the conventional DD approach-based system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.9 no.5
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• pp.12-18
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• 1972

The relation between output SNR and mth harmonic generation is determined for nonlinear system of zero memory type, half wave and the nth power law devices with narrow band form of the unmodulated sinusoidal wave plus zero mean and stationary gaussian noise input. It is found that the optimum generation condition for harmonic component at a small input of SNR is m and n equal 2, while for large input SNR is always n equals 2.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.209-210
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• 1998

Noise characteristics of preamplifier, the most essential part of on-chip signal processing circuitry for the active semiconductor neural probe, is the important factor determining the overall signal-to-noise-ratio (SNR). We present a systematic design method for the optimization of SNR, based on the spectral characteristics of the electrode, circuit noise and extracelluar action potential. Analytical expression is derived to calculate total output noise power. Output SNR of 2-stage CMOS preamplifier is tailored to meet the given specification while the layout area is minimized.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.26-30
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• 2019

This paper proposes a new voice activity detection (VAD) method which is based on SNR and non-intrusive speech intelligibility estimation. In the conventional SNR-based VAD methods, voice activity probability is obtained by estimating frame-wise SNR at each spectral component. However these methods lack performance in various noisy environments. We devise a hybrid VAD method that uses non-intrusive speech intelligibility estimation as well as SNR estimation, where the speech intelligibility score is estimated based on deep neural network. In order to train model parameters of deep neural network, we use MFCC vector and the intrusive speech intelligibility score, STOI (Short-Time Objective Intelligent Measure), as input and output, respectively. We developed speech presence measure to classify each noisy frame as voice or non-voice by calculating the weighted average of the estimated STOI value and the conventional SNR-based VAD value at each frame. Experimental results show that the proposed method has better performance than the conventional VAD method in various noisy environments, especially when the SNR is very low.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6A
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• pp.511-518
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• 2007

One of the major issues that has to be carefully considered when upgrading current transport network capacity, is network scalability. A novel full-meshed connected ring expansion methodology and planning tool have been proposed. A 3 to 15 node expansion ring has been studied by demonstrating a dramatic system SNR improvement when the proposed planning tool was used. The results are that node output signal and optical SNR have been improved from -16dBm/10dB to +005dBm/21dB by NPOT.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1571-1576
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• 2013

This paper proposes an improvement algorithm of signal-to-noise ratios (SNRs) for speech signals under noisy environments. The proposed algorithm first estimates the SNRs in a low SNR, mid SNR and high SNR areas, in order to improve the SNRs in the speech signal from background noise, such as white noise and car noise. Thereafter, this algorithm subtracts the noise signal from the noisy speech signal at each bands using a spectrum sharpening method. In the experiment, good signal-to-noise ratios (SNR) are obtained for white noise and car noise compared with a conventional spectral subtraction method. From the experiment results, the maximal improvement in the output SNR results was approximately 4.2 dB and 3.7 dB better for white noise and car noise compared with the results of the spectral subtraction method, in the background noisy environment, respectively.