• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.169-172
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• 2000

본 논문에서는 차량 환경에서 핸즈프리 단말기를 위한 잔향반향제거 방법을 제안한다. 제안된 방법은 기존의 음향반향제거와 잡음제거의 결합구조에 근거하며, 음성신호의 스펙트럼 특성을 배경잡음화함으로써 잔여 반향제거 성능을 향상시킨다. 일반적으로 음향반향제거에서 실제 충격응답보다 적은 차수의 적응필터를 이용할 경우 잔여반향의 전력이 증가하며, 잡음제거기법을 적용하여 잔여반향성분을 줄일 수 있다. 음성신호가 입력되는 음향반향제거기의 잔여반향을 효과적으로 제거하기 위해 음성신호의 AR 스펙트럼에 따른 역필터링을 수행함으로써 잡음제거기에 의한 잔여반향제거 성능을 향상시킬 수 있다. 제안된 기법은 현재 상용화되고 있는 이동통신용 음성부호화기에 포함된 잡음제거기법과 결합하여 사용할 경우 매우 적은 부가 계산량만으로 구현할 수 있다.

• Journal of Internet Computing and Services
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• v.19 no.3
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• pp.49-56
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• 2018

Euclidean distance (ED) between error distribution and Dirac delta function has been used as an efficient performance criterion in impulsive noise environmentsdue to the outlier-cutting effect of Gaussian kernel for error signal. The gradient of ED for its minimization has two components; $A_k$ for kernel function of error pairs and the other $B_k$ for kernel function of errors. In this paper, it is analyzed that the first component is to govern gathering close together error samples, and the other one $B_k$ is to conduct error-sample concentration on zero. Based upon this analysis, it is proposed to normalize $A_k$ and $B_k$ with power of inputs which are modified by kernelled error pairs or errors for the purpose of reinforcing their roles of narrowing error-gap and drawing error samples to zero. Through comparison of fluctuation of steady state MSE and value of minimum MSE in the results of simulation of multipath equalization under impulsive noise, their roles and efficiency of the proposed normalization method are verified.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.995-1000
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• 2016

The maximum cross-correntropy (MCC) algorithm with a set of random symbols keeps its optimum weights undisturbed from impulsive noise unlike MSE-based algorithms and its main factor has been known to be the input magnitude controller (IMC) that adjusts the input intensity according to error power. In this paper, a normalization of the step size of the MCC algorithm by the power of IMC output is proposed. The IMC output power is tracked recursively through a single-pole low-pass filter. In the simulation under impulsive noise with two different multipath channels, the steady state MSE and convergence speed of the proposed algorithm is found to be enhanced by about 1 dB and 500 samples, respectively, compared to the conventional MCC algorithm.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.636-636
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• 2006

• The Journal of the Acoustical Society of Korea
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• v.33 no.5
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• pp.335-340
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• 2014

In this paper, we propose a new sign subband adaptive filter to improve the convergence rate of the conventional sign subband adaptive filter which has been proposed to deal with colored input signal under the environment with impulsive noise. The existing sign subband adaptive filter does not increase the convergence speed by increasing the number of subband because each subband input signal is normalized by $l_2-norm$ of all of the subband input signals. We devised a new sign subband adaptive filter that normalizes each subband input signal with $l_2-norm$ of each subband input signal and increases the convergence rate by increasing the number of subband. We carried out a performance comparison of the proposed algorithm with the existing sign subband adaptive filter using a system identification model. It is shown that the proposed algorithm has faster convergence rate than the existing sign subband adaptive filter.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.49-55
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• 2020

Information theoretic learning (ITL) methods based on random symbols (RS) use a set of random symbols generated according to a target distribution and are designed nonparametrically to minimize the cost function of the Euclidian distance between the target distribution and the input distribution. One drawback of the learning method is that it can not utilize the input power statistics by employing a constant stepsize for updating the algorithm. In this paper, it is revealed that firstly, information potential input (IPI) plays a role of input in the cost function-derivative related with information potential output (IPO) and secondly, input itself does in the derivative related with information potential error (IPE). Based on these observations, it is proposed to normalize the step-size with the statistically varying power of the two different inputs, IPI and input itself. The proposed algorithm in an communication environment of impulsive noise and multipath fading shows that the performance of mean squared error (MSE) is lower by 4dB, and convergence speed is 2 times faster than the conventional methods without step-size normalization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.627-632
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• 2021

ITL (information-theoretic learning) has been applied successfully to adaptive signal processing and machine learning applications, but there are difficulties in deciding the kernel size, which has a great impact on the system performance. The correntropy algorithm, one of the ITL methods, has superior properties of impulsive-noise robustness and channel-distortion compensation. On the other hand, it is also sensitive to the kernel sizes that can lead to system instability. In this paper, considering the sensitivity of the kernel size cubed in the denominator of the cost function slope, a new adaptive kernel estimation method using the rate of change in error power in respect to the kernel size variation is proposed for the correntropy algorithm. In a distortion-compensation experiment for impulsive-noise and multipath-distorted channel, the performance of the proposed kernel-adjusted correntropy algorithm was examined. The proposed method shows a two times faster convergence speed than the conventional algorithm with a fixed kernel size. In addition, the proposed algorithm converged appropriately for kernel sizes ranging from 2.0 to 6.0. Hence, the proposed method has a wide acceptable margin of initial kernel sizes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.9-14
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• 2020

In this paper, Qualification Model of frequency synthesizer is designed for X-band SAR system and performed electrical and environment test. Designed frequency synthesizer generate 13.65 GHz with very low phase noise performance. The integrated phase noise from 10Hz to 1MHz is -37.91 dBc. IRF performances are analyzed according to phase noise and jitter. Also, thermal and structure analysis are achieved for stable operation in space environment. Designed frequency synthesizer is consist of 2 modules of 6U size and generate L-band, C-band, Ku-band. The result of this study would enhance the design ability of RF module and help the frequency synthesizer design for SAR payload system.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2983-2985
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• 2005

There are many factors to degrade the performance of power-line communication systems such as multi-path fading, attenuation, colored and impulsive noise, and interference. Most of all, impulsive noise is generated by switching operation of many power supply units and equipments, and it causes both burst error and random error as the pattern of generation. In this paper, the variations of performance for RS convolutional concatenated coded system are simulated and analysed with the several parameters over impulsive noise channel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.6
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• pp.1522-1532
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• 1996

In this paper, we compare the performance of channel estimators with the L$_{1}$-norm and L$_{2}$-norm criteria in impulaive noise environment, and show than the L$_{1}$-norm criterion is appropriate for that situation. Also, it is shown that the performance of the conventional maximum likelihood sequence detector(MLSD) can be improved by applying the same principle to mobile channels. That is, the performance of the conventional MLSD, which is known to be optimal under the Gaussian noise assumption, degrades in the impulsive noise of radio mobile communication channels. So, we proposed the MLSD which can reduce the effect of impulsive noise effectively by applying the results of channel estimators. Finally, it is confirmed by computer simulation that the performance of MLSD is significantly affected depending on the types of branch metrics, and that, in the impulsive noise environments, the proposed one with new branch metrics performs better thatn the conventional branch metric, l y(k)-s(k) l$^{[-992]}$ .