• Title/Summary/Keyword: Least mean square

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Adaptive Hybrid Beamformer Suitable for Fast Fading (고속 페이딩에 적합한 적응 하이브리드 빔형성기)

  • Ahn Jang Hwan;Han Dong Seog
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.42 no.2 s.332
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    • pp.49-59
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    • 2005
  • An adaptive hybrid beamformer is proposed to improve the reception performance of the advanced television system committee (ATSC) digital television (DTV) in a mobile environment. Dynamic multipaths and Doppler shifts severely degrade the reception performance of the ATSC DTV receiver. Accordingly, a hybrid beamformer, called a Capon and least mean square (CLMS) beamformer, is presented that uses direction of arrival (DOA) information and the least mean square (LMS) beamforming algorithm. The proposed CLMS algerian efficiently removes dynamic multipaths and compensates for the phase distortion caused by Doppler shifts in mobile receivers. After the CLMS beamformer is operated, the subsequent use of an equalizer removes any residual multipath effects, thereby significantly improving the performance of DTV receivers. The performances of the proposed CLMS, Capon, and LMS beamformersare compared based on computer simulations. In addition, the overall performance of the CLMS beamformer followed by an equalizer is also considered.

Variable Step LMS Algorithm using Fibonacci Sequence (피보나치 수열을 활용한 가변스텝 LMS 알고리즘)

  • Woo, Hong-Chae
    • Journal of the Institute of Convergence Signal Processing
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    • v.19 no.2
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    • pp.42-46
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    • 2018
  • Adaptive signal processing is quite important in various signal and communication environments. In adaptive signal processing methods since the least mean square(LMS) algorithm is simple and robust, it is used everywhere. As the step is varied in the variable step(VS) LMS algorithm, the fast convergence speed and the small excess mean square error can be obtained. Various variable step LMS algorithms are researched for better performances. But in some of variable step LMS algorithms the computational complexity is quite large for better performances. The fixed step LMS algorithm with a low computational complexity merit and the variable step LMS algorithm with a fast convergence merit are combined in the proposed sporadic step algorithm. As the step is sporadically updated, the performances of the variable step LMS algorithm can be maintained in the low update rate using Fibonacci sequence. The performances of the proposed variable step LMS algorithm are proved in the adaptive equalizer.

Implementation of Adaptive Noise Canceller Using Instantaneous Gain Control Algorithm (순시 이득 조절 알고리즘을 이용한 적응 잡음 제거기의 구현)

  • Lee, Jae-Kyun;Kim, Chun-Sik;Lee, Chae-Wook
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.6
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    • pp.95-101
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    • 2009
  • Among the adaptive noise cancellers (ANC), the least mean square (LMS) algorithm has probably become the most popular algorithm because of its robustness, good tracking properties, and simplicity of implementation. However, it has non-uniform convergence and a trade-off between the rate of convergence and excess mean square error (EMSE). To overcome these shortcomings, a number of variable step size least mean square (VSSLMS) algorithms have been researched for years. These LMS algorithms use a complex variable step method approach for rapid convergence but need high computational complexity. A variable step approach can impair the simplicity and robustness of the LMS algorithm. The proposed instantaneous gain control (IGC) algorithm uses the instantaneous gain value of the original signal and the noise signal. As a result, the IGC algorithm can reduce computational complexity and maintain better performance.

Speech Enhancement Using the Adaptive Noise Canceling Technique with a Recursive Time Delay Estimator (재귀적 지연추정기를 갖는 적응잡음제거 기법을 이용한 음성개선)

  • 강해동;배근성
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.7
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    • pp.33-41
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    • 1994
  • A single channel adaptive noise canceling (ANC) technique with a recursive time delay estimator (RTDE) is presented for removing effects of additive noise on the speech signal. While the conventional method makes a reference signal for the adaptive filter using the pitch estimated on a frame basis from the input speech, the proposed method makes the reference signal using the delay estimated recursively on a sample-by-sample basis. As the RTDEs, the recursion formulae of autocorrelation function (ACF) and average magnitude difference function (AMDF) are derived. The normalized least mean square (NLMS) and recursive least square (RLS) algorithms are applied for adaptation of filter coefficients. Experimental results with noisy speech demonstrate that the proposed method improves the perceived speech quality as well as the signal-to-noise ratio and cepstral distance when compared with the conventional method.

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A New Stylization Method using Least-Square Error Minimization on Segmental Pitch Contour (최소 자승오차 방식을 이용한 세그먼트 피치패턴의 정형화)

  • 이정철
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1994.06c
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    • pp.107-110
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    • 1994
  • In this paper, we describe the features of the fundamental frequency contour of Korean read speech, and propose a new stylization method to characterize the Fø pattern of segments. Our algorithm consists of three stylization processes : the segment level, the syllable level, and the sord level. For stylization of Fø contour in the segment level , we applied least square error minimization method to determine Fø values at initial, medial, and final position in a segment. In the syllable level, we determine the stylized Fø pattern of a syllable using the mean Fø value of each word and style information for each word, syllable and segment, we reconstruct Fø contour of sentences. The simulation results show that the error is less than 10% of the actual Fø contour for each sentence. In perception test, there is little difference between the synthesized speech with the original difference between the synthesized speech with the original Fø contour and the synthesized speech with the stylized Fø contour.

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Unsupervised Endmember Selection Optimization Process based on Constrained Linear Spectral Unmixing of Hyperion Image (Hyperion 영상의 제약선형분광혼합분석 기반 무감독 Endmember 추출 최적화 기법)

  • Choi Jae-Wan;Kim Yong-Il;Yu Ki-Yun
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2006.04a
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    • pp.211-216
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    • 2006
  • The Constrained Linear Spectral Unmixing(CLSU) is investigated for sub-pixel image processing, Its result is the abundance map which mean fractions of endmember existing in a mixed pixel. Compared to the Linear Spectral Unmixing using least square method, CLSU uses the NNLS (Non-Negative Least Square) algorithm to guarantee that the estimated fractions are constrained. But, CLSU gets Into difficulty in image processing due to select endmember at a user's disposition. In this study, endmember selection optimization method using entropy in the error-image analysis is proposed. In experiments which is used hyperion image, it is shown that our method can select endmember number than CLSU based on unsupervised endemeber selection.

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Adaptive Equalizer Design Using Modified Escalator Algorithm (변형된 에스컬레이터 알고리즘을 이용한 적응 등화기 설계)

  • Cho, Seong-Hun;Yoo, Kyung-Yul
    • Proceedings of the KIEE Conference
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    • 1999.11c
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    • pp.760-762
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    • 1999
  • 본 논문에서는 기존의 적응필터인 LMS(Least Mean Square)와 RLS(Recursive Least Square)의 수렴속도의 향상과 안정성을 개선하기 위한 방안을 제안하였다. 제안된 알고리즘은 기존의 시간영역 LMS 알고리즘보다 상당히 빠른 수렴속도를 보일 수 있도록 설계하였다. RLS 알고리즘는 역행렬연산으로 인한 연산량이 많고 자기상관행렬이 positive definite 특성을 잃어버릴 경우 시스템이 수치적으로 불안정하게 되어 발산하는 단점이 있다. 이런한 단점을 보완하기 위해 제안된 알고리즘을 사용하였다. 기존의 알고리즘은 전력 정규화 과정에서 입력신호의 변환이 백색화가 완전히 이루어지지 않게 되어 자기상관행렬이 순수한 대각행렬이 되지 않는 단점을 지니고 있으나, 본 연구에서는 이러한 대각화 과정에서 좀더 많은 정보를 포함하도록 설계하였다. 아울러 제안된 알고리즘을 적응 등화기에 적용하여 수렴속도가 개선됨을 검증하였다.

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Further Results on Piecewise Constant Hazard Functions in Aalen's Additive Risk Model

  • Uhm, Dai-Ho;Jun, Sung-Hae
    • The Korean Journal of Applied Statistics
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    • v.25 no.3
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    • pp.403-413
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    • 2012
  • The modifications suggested in Uhm et al. (2011) are studied using a partly parametric version of Aalen's additive risk model. A follow-up time period is partitioned into intervals, and hazard functions are estimated as a piecewise constant in each interval. A maximum likelihood estimator by iteratively reweighted least squares and variance estimates are suggested based on the model as well as evaluated by simulations using mean square error and a coverage probability, respectively. In conclusion the modifications are needed when there are a small number of uncensored deaths in an interval to estimate the piecewise constant hazard function.

Acceleration Feedforward Control in Active Magnetic Bearing System Subject to Base Motion by Filtered-x LMS Algorithm (베이스 가진을 받는 능동자기베어링 시스템에서 Filtered-x LMS 알고리듬을 이용한 가속도 앞먹임 제어)

  • Kang, Min-Sig
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.10
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    • pp.1712-1719
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    • 2003
  • This paper concerns on application of active magnetic bearing(AMB) system to levitate the elevation axis of an electro-optical sight mounted on moving vehicles. In such a system, it is desirable to retain the elevation axis within the predetermined air-gap while the vehicle is moving. An optimal base acceleration feedforward control is proposed to reduce the base motion response. In the consideration of the uncertainty of the system model, a filtered-x least-mean-square(FXLMS) algorithm is used to estimate the frequency response function of the feedforward control which cancels base motions. The frequency response function is fitted to an optimal feedforward control. Experimental results demonstrate that the proposed control reduces the air-gap deviation to 27.7% that by feedback control alone.

Location Estimation for Multiple Targets Using Expanded DFS Algorithm (확장된 깊이-우선 탐색 알고리듬을 적용한 다중표적 위치 좌표 추정 기법)

  • Park, So Ryoung;Noh, Sanguk
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38C no.12
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    • pp.1207-1215
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    • 2013
  • This paper proposes the location estimation techniques of distributed targets with the multi-sensor data perceived through IR sensors of the military robots in consideration of obstacles. In order to match up targets with measured azimuths, to add to the depth-first search (DFS) algorithms in free-obstacle environment, we suggest the expanded DFS (EDS) algorithm including bypass path search, partial path search, middle level ending, and the supplementation of decision metric. After matching up targets with azimuths, we estimate the coordinate of each target by obtaining the intersection point of the azimuths with the least square error (LSE) algorithm. The experimental results show the error rate of estimated location, mean number of calculating nodes, and mean distance between real coordinates and estimated coordinates of the proposed algorithms.