• Journal of information and communication convergence engineering
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• 제8권2호
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• pp.155-158
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• 2010

In this article, we proposed a new interference canceller using the adaptive algorithm. We designed constant modulus algorithm-correlation normailized least mean square (CMA-CNLMS) for wireless system. This structure is normalized LMS algorithm using correlation between the desired and input signal for cancelling the interference signals in the wideband code division multiple access (WCDMA) system. We showed that the proposed algorithm could improve the Mean Square Error (MSE) performance of LMS algorithm. MATLAB (Matrix Laboratory) is employed to analyze the proposed algorithm and to compare it with the experimental results. The MSE value of the LMS with mu=0.0001 was measured as - 12.5 dB, and that of the proposed algorithm was -19.5 dB which showed an improvement of 7dB.

• 한국군사과학기술학회지
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• 제16권4호
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• pp.537-544
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• 2013

This paper proposes a recursive localized Normalized Mutual Information(NMI) algorithm to overcome shortcomings of the conventional NMI algorithm and the localized NMI algorithm which proposed before. The localized NMI algorithm divides images into few fixed size segments and applies NMI algorithm to each segments. By extension, the proposed algorithm uses variable size segments using its characteristic. Dividing each segment recursively, the algorithm selects a suitable segment size and improves a performance of the image registration. Experimental result shows the performance of the proposed algorithm.

• 전자공학회논문지
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• 제52권2호
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• pp.148-161
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• 2015

자동차 시장의 성장과 함께 차량에 카메라가 사용되는 사례가 늘고 있으며 영상 처리 기술의 중요성이 증가하고 있다. 또한, 차량 전장 시스템 기술 역시 급속도로 성장을 하고 있으며, 특히 차선이탈경보시스템(Lane Departure Warning System, LDWS)과 관련된 기술들이 다방면으로 개발 중이다. 본 논문에서는 기존의 방법보다 더 높은 차선 인식률을 검출하기 위해 촬영된 영상에서 먼저 Normalized Luminance Descriptor와 Normalized Contrast Descriptor값을 각각 연산하여, 두 값의 상관관계를 통해 Normalized Image Quality값을 조절하여 영상의 감마값을 조절한다. 그 뒤 다중의 관심영역을 통해 다중 영역에서 선택적 허프변환 알고리즘을 통한 차선 검출 알고리즘을 적용하여 차량 전방의 차선을 인식한다. 제안하는 알고리즘은 평균 27 Frame/sec와 $640{\times}480$ 해상도에서 검증 과정을 가졌다. 결과적으로 주 야간 및 심야를 포함한 도로들에서 평균 97% 이상의 차선 인식률을 보였으며 커브구간이나 차도 내 표식이 많은 구간에서도 성공적인 차선 인식을 보인다.

• The Journal of the Acoustical Society of Korea
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• 제27권1E호
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• pp.1-10
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• 2008

A noise suppression algorithm is proposed for nonstationary noisy environments. The proposed algorithm is different from the conventional approaches such as the spectral subtraction algorithm and the minimum statistics noise estimation algorithm in that it classifies speech and noise signals in time-frequency bins. It calculates the ratio of the variance of the noisy power spectrum in time-frequency bins to its normalized time-frequency average. If the ratio is greater than an adaptive threshold, speech is considered to be present. Our adaptive algorithm tracks the threshold and controls the trade-off between residual noise and distortion. 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 simplicity and light computational load for estimating the noise. This algorithm reduces the residual noise significantly, and is superior to the conventional methods.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.278-281
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• 2009

In this paper, we propose a fast partial distortion algorithm using normalized dithering matching scan to get uniform distribution of partial distortion which can reduce only unnecessary computation significantly. Our algorithm is based on normalized dithering order matching scan and calibration of threshold error using LOG value for each sub-block continuously for efficient elimination of unlike candidate blocks while keeping the same prediction quality compared with the full search algorithm. Our algorithm reduces about 60% of computations for block matching error compared with conventional PDE (partial distortion elimination) algorithm without any prediction quality, and our algorithm will be useful to real-time video coding applications using MPEG-4 AVC or MPEG-2.

• ETRI Journal
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• 제45권3호
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• pp.379-393
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• 2023

Underwater communication (UWC) is widely used in coastal surveillance and early warning systems. Precise channel estimation is vital for efficient and reliable UWC. The sparse direct-adaptive filtering algorithms have become popular in UWC. Herein, we present an improved adaptive convex-combination method for the identification of sparse structures using a reweighted normalized leastmean-square (RNLMS) algorithm. Moreover, to make RNLMS algorithm independent of the reweighted l₁-norm parameter, a modified sparsity-aware adaptive zero-attracting RNLMS (AZA-RNLMS) algorithm is introduced to ensure accurate modeling. In addition, we present a quantitative analysis of this algorithm to evaluate the convergence speed and accuracy. Furthermore, we derive an excess mean-square-error expression that proves that the AZA-RNLMS algorithm performs better for the harsh underwater channel. The measured data from the experimental channel of SPACE08 is used for simulation, and results are presented to verify the performance of the proposed algorithm. The simulation results confirm that the proposed algorithm for underwater channel estimation performs better than the earlier schemes.

• 한국정보전자통신기술학회논문지
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• 제8권1호
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• pp.45-50
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• 2015

본 논문은 능동 소음 제어를 위한 적응 알고리즘들의 성능을 비교함으로써 효과적인 적응 알고리즘을 보인다. 일반적인 적응 알고리즘으로는 normalized least mean square (NLMS) 알고리즘이 있다. NLMS는 구조가 간단하고 수렴 속도가 빠르다는 장점이 있어서 널리 사용되고 있다. 하지만 상관도가 높은 신호에 대해서는 수렴 성능이 떨어지는 문제가 발생한다. 이에 수렴 성능을 개선하기 위해 affine projection (AP) 알고리즘을 사용하고 있다. 하지만 연산량의 문제로 AP 알고리즘의 사용이 제한적이다. 이러한 사실을 바탕으로 협대역 소음 제어를 위한 능동 소음 제어 시스템에서 NLMS와 AP 알고리즘을 연산량과 수렴 성능을 비교함으로써 효과적인 알고리즘을 도출하였다. 실험을 통해 NLMS와 AP 알고리즘의 소음 제어 성능이 차이가 크게 발생하지 않는 것을 확인함으로써 NLMS가 AP 알고리즘에 비해 소음 제어에 효과적임을 확인하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계학술대회논문집
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• pp.551-554
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• 2005

The method of the reduction of the automotive induction noise can be classified by the method of passive control and the method of active control. However, the passive control method has a demerit to reduce the effect of noise reduction at low frequency (below 500Hz) range and to be limited by a space of the engine room. Whereas, the active control method can overcome the demerit of passive control method. The algorithm of active control is mostly used the LMS (Least-Mean-Square) algorithm because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, When the Filtered-X LMS (FXLMS) algorithm is applied to an ANC system. However, the convergence performance of LMS algorithm goes bad when the FXLMS algorithm is applied to an active control of the induction noise under rapidly accelerated driving conditions. Thus Normalized FXLMS algorithm was developed to improve the control performance under the rapid acceleration. The advantage of Normalized FXLMS algorithm is that the step size is no longer constant. Instead, it varies with time. But there is one additional practical difficulty that can arise when a nonstationary input is used. If the input is zero for consecutive samples, then the step size becomes unbounded. So, in order to solve this problem. the Correlation FXLMS algorithm was developed. The Correlation FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Correlation FXLMS Is presented in comparison with that of the other FXLMS algorithms based on computer simulations.

• 전자공학회논문지A
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• 제33A권4호
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• pp.18-26
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• 1996

In this paper we propose a new dual structured tap selection algorithm for voice echo canceller in digital cellular communication system, investigating adaptive filtering algorithms for echo cancellation in long distance telephony or mobile communication system. The proposed algorithm has a two-stage processing structure that after a dispersive region in an impulse response of an echo path is found out, the tap coefficients of a short length filter are adjusted adaptively for the region, because the impuse response has a very little portion of the dispersion. Simulation results show that the proposed algorithm with 256 taps gives a performance of convergence speed superior to both full-tap normalized least mean with 256 taps gives a performance of convergence speed superior to both full-tap normalized least mean square (NLMS) and a scrub taps waiting in a queue (STWQ) algorithms by about eighty per cent, also to a tap selection algorithm by about twenty per cent. And the resutls diplay that if the more tap coefficients are used due to a long delayed dispersive zone, the proposed algorithm produces the better performance.

• Journal of Electrical Engineering and information Science
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• 제1권2호
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• pp.119-124
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• 1996

Variable step size LMS(VS-LMS) algorithms improve performance of LMS algorithm by means of varying the step size. This paper presents a new VS-LMS algorithm using normalized absolute estimation error. Normalizing the estimation error to the expected valus of the desired signal, we determined the step size using the relative size of estimation error, Because parameters and computational load are less, our algorithm is easy to implement in hardware. The performance of the proposed algorithm is analyzed theoretically and estimated through simulations. Based on the theoretical analysis and computer simulations, the proposed algorithm is shown to be effective compared to conventional VS-LMS algorithms.