• 한국컴퓨터정보학회논문지
• /
• 제25권5호
• /
• pp.65-72
• /
• 2020

본 논문에서는, 지난 연구에서 제안한 D2D 전력제어 알고리즘의 성능 개선을 위하여, 채널추정 에러를 보상하는 세 가지 수정 D2D 전력제어 알고리즘을 제안한다. 또한, 제안하는 세 가지 수정 D2D 전력제어 알고리즘을 채널추정 에러 환경에서 성능평가를 진행한다. 실제 채널환경에서는 채널추정 에러가 빈번하게 발생한다. 지난 연구에서는 채널추정 에러가 없는 환경을 가정하고 제안된 D2D 전력제어 알고리즘이 채널추정 에러 환경에서 성능 문제가 있음을 확인하었다. 세 가지 수정 D2D 전력제어 알고리즘은 1)재전송, 2)신호대 간섭비 여유, 3)재전송과 신호대 간섭비 병합을 기반으로 한다. 실험 결과 재전송과 신호대 간섭비 병합기법이 채널추정 에러를 보상하는 데 소모하는 전송전력과 지연 관점에서 가장 좋은 성능을 보임을 확인하였다.

• 한국전자통신학회논문지
• /
• 제6권5호
• /
• pp.723-729
• /
• 2011

본 논문에서는 레일리(Rayleigh) 페이딩 채널 환경에서 MMSE-OSUC 수신기 알고리즘을 적용한 MIMO 시스템의 성능을 시뮬레이션을 통해 평가하였다. 변조 기법은 BPSK, QPSK, 16QAM, 64QAM으로 각각 나누어 시뮬레이션을 수행하였고, 프레임의 길이는 100 심볼로 설정하였다. 먼저 송신단에서 채널상태정보를 모르는 경우의 MIMO 시스템의 채널 용량을 이론적으로 산출하였다. 성능 해석 결과, 채널 용량은 채널의 함수이므로 MIMO 시스템의 채널 용량은 채널의 특성에 따라 큰 영향을 받음을 알 수 있었다. 다음으로 MIMO 채널에서의 성능 향상을 위해 MIMO 시스템에 적용되는 기술의 각 알고리즘을 분석하였다. 성능 해석 결과, MMSE-OSUC 수신기 알고리즘을 적용한 경우가 기존 ZF-OSUC 수신기 알고리즘을 적용한 경우보다 전반적으로 성능은 우수하지만, 성좌도가 큰 변조 기법을 사용할수록 그 성능 차이가 감소함을 알 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권1호
• /
• pp.168-182
• /
• 2020

Spoofing attacks, especially replay attacks, pose great security challenges to automatic speaker verification (ASV) systems. Current works on replay attacks detection primarily focused on either developing new features or improving classifier performance, ignoring the effects of feature variability, e.g., the channel variability. In this paper, we first establish a mathematical model for replay speech and introduce a method for eliminating the negative interference of the channel. Then a novel feature is proposed to detect the replay attacks. To further boost the detection performance, four post-processing methods using normalization techniques are investigated. We evaluate our proposed method on the ASVspoof 2017 dataset. The experimental results show that our approach outperforms the competing methods in terms of detection accuracy. More interestingly, we find that the proposed normalization strategy could also improve the performance of the existing algorithms.

• 말소리와 음성과학
• /
• 제3권2호
• /
• pp.71-78
• /
• 2011

In this paper, we propose an approach which constructs classifier ensembles of various channel compensation and feature enhancement methods. CMN and CMVN are used as channel compensation methods. PCA, kernel PCA, greedy kernel PCA, and kernel multimodal discriminant analysis are used as feature enhancement methods. The proposed ensemble system is constructed with the combination of 15 classifiers which include three channel compensation methods (including 'without compensation') and five feature enhancement methods (including 'without enhancement'). Experimental results show that the proposed ensemble system gives highest average speaker identification rate in various environments (channels, noises, and sessions).

• 대한음성학회지:말소리
• /
• 제48호
• /
• pp.155-173
• /
• 2003

This paper proposes a noise reduction-based speech detection method under telephone channel environments. We adopt the AURORA front-end noise reduction algorithm based on the two-stage mel-warped Wiener filter approach as a preprocessor for the frequency domain speech detector. The speech detector utilizes mel filter-bank based useful band energies as its feature parameters. The preprocessor firstly removes the adverse noise components on the incoming noisy speech signals and the speech detector at the next stage detects proper speech regions for the noise-reduced speech signals. Experimental results show that the proposed noise reduction-based speech detection method is very effective in improving not only the performance of the speech detector but also that of the subsequent speech recognizer.

• Journal of Communications and Networks
• /
• 제16권3호
• /
• pp.264-269
• /
• 2014

We consider transmission over body area networks. Due to the difficulty in assessing an accurate statistical model valid for multiple scenarios, we advocate a system design technique favoring robustness. Our approach, which is based on results in [12] and generalizes them, examines the variation of a performance metric when the nominal statistical distribution of fading is replaced by the worst distribution within a given Kullback-Leibler divergence from it. The sensitivity of the performance metric to the divergence from the nominal distribution can be used as an indication of the design robustness. This concept is applied by evaluating the error probability of binary uncoded modulation and the outage probability-the first parameter is useful to assess system performance with no error-control coding, while the second reflects the performance when a near-optimal code is used. The usefulness of channel coding can be assessed by comparing its robustness with that of uncoded transmission.

• Transactions on Control, Automation and Systems Engineering
• /
• 제3권4호
• /
• pp.250-256
• /
• 2001

This paper deals with a design problem of a decentralized controller with a strongly connected two-input two-output multivariable system. To this end, we present a classical design approach which consists of two main steps: one is to decompose the multivariable plant into two single-input single-output systems by means of the Individual Channel Design (ICD) concept, the other is to design controller of each channel by the Coefficient Diagram Method (CDM) so that it satisfies, especially, time domain specifications such as settling time, overshoot etc.. A design procedure was proposed and then was applied to a 2$\times$2 hot rolling mill plant. Simulation results showed that the proposed method has excellent control performances.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
• /
• pp.1677-1683
• /
• 2006

Color image segmentation is useful for fast retrieval in large image database. For that purpose, new image segmentation technique based on the probability of pixel distribution in the image is proposed. Color image is first divided into R, G, and B channel images. Then, pixel distribution from each of channel image is extracted to select to which it is similar among the well known probabilistic distribution function-Weibull, Exponential, Beta, Gamma, Normal, and Uniform. We use sum of least square error to measure of the quality how well an image is fitted to distribution. That P.d.f has minimum score in relation to sum of square error is chosen. Next, each image is quantized into 4 gray levels by applying thresholds to the c.d.f of the selected distribution of each channel. Finally, three quantized images are combined into one color image to obtain final segmentation result. To show the validity of the proposed method, experiments on some images are performed.

• 말소리와 음성과학
• /
• 제4권4호
• /
• pp.87-92
• /
• 2012

Speech enhancement aims to improve speech quality by removing background noise from noisy speech. Independent vector analysis is a type of frequency-domain independent component analysis method that is known to be free from the frequency bin permutation problem in the process of blind source separation from multi-channel inputs. This paper proposed a new method of microphone array based speech enhancement that combines independent vector analysis and beamforming techniques. Independent vector analysis is used to separate speech and noise components from multi-channel noisy speech, and delay-sum beamforming is used to determine the enhanced speech among the separated signals. To verify the effectiveness of the proposed method, experiments for computer simulated multi-channel noisy speech with various signal-to-noise ratios were carried out, and both PESQ and output signal-to-noise ratio were obtained as objective speech quality measures. Experimental results have shown that the proposed method is superior to the conventional microphone array based noise removal approach like GSC beamforming in the speech enhancement.

• 한국통신학회논문지
• /
• 제28권7C호
• /
• pp.705-711
• /
• 2003

This paper studies the application of a fuzzy-ARTMAP neural network to digital communications channel equalization. This approach provides new solutions for solving the problems, such as complexity and long training, which found when implementing the previously developed neural-basis equalizers. The proposed fuzzy-ARTMAP equalizer is fast and easy to train and includes capabilities not found in other neural network approaches; a small number of parameters, no requirements for the choice of initial weights, automatic increase of hidden units, no risk of getting trapped in local minima, and the capability of adding new data without retraining previously trained data. In simulation studies, binary signals were generated at random in a linear channel with Gaussian noise. The performance of the proposed equalizer is compared with other neural net basis equalizers, specifically MLP and RBF equalizers.