• Title/Summary/Keyword: 최소제곱오차 알고리즘

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Optimization of Transmit Power, Receiver Filter, and Access Point Selection (전송전력, 수신필터, 엑세스 포인트 선택 최적화)

  • Oh, Changyoon
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.07a
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    • pp.201-202
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    • 2021
  • 본 논문에서는 다중 엑세스 포인트 환경에서 전송전력, 수신필터, 엑세스 포인트 선정 최적화 알고리즘을 제안한다. 최종목적은 신호대간섭비를 유지하면서, 전송전력의 총합을 최소화하는 것이다. 증명을 통해서 제안하는 알고리즘은 최소전력에 수렴함을 보인다. 제안하는 알고리즘이 기존에 제안되었던 두 개의 알고리즘인 1)전송전력과 최소제곱평균오차(MMSE) 수신필터 최적화 알고리즘, 2) 전송전력 최적화 알고리즘보다 전송전력 소모량에서 성능이 우수함을 실험을 통해서 확인하였다.

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The Comparison of the Performance for LMS Algorithm Family Using Asymptotic Relative Efficiency (점근상대효율을 이용한 최소평균제곱 계열 적응여파기의 성능 비교)

  • Sohn, Won
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.37 no.6
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    • pp.70-75
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    • 2000
  • This paper examines the performance of adaptive filtering algorithms in relation to the asymptotic relative efficiency (ARE) of estimators. The adaptive filtering algorithms are Hybrid II and modified zero forcing (MZF) algorithms. The Hybrid II and MZF algorithms are simplified forms of the LMS algorithm, which use the polarity of the input signal, and polarities of the error and input signals, respectively. The ARE of estimators for each algorithm is analyzed under the condition of the same convergence speed. Computer simulations for adaptive equalization are performed to check the validity of the theory. The explicit expressions for the ARE values of the Hybrid II and MZF algorithms are derived, and its results have similar values to the results of computer simulation. It also revealed that the ARE values depend on the correlation coefficients between input signal and error signal.

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Incremental Linear Discriminant Analysis for Streaming Data Using the Minimum Squared Error Solution (스트리밍 데이터에 대한 최소제곱오차해를 통한 점층적 선형 판별 분석 기법)

  • Lee, Gyeong-Hoon;Park, Cheong Hee
    • Journal of KIISE
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    • v.45 no.1
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    • pp.69-75
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    • 2018
  • In the streaming data where data samples arrive sequentially in time, it is difficult to apply the dimension reduction method based on batch learning. Therefore an incremental dimension reduction method for the application to streaming data has been studied. In this paper, we propose an incremental linear discriminant analysis method using the least squared error solution. Instead of computing scatter matrices directly, the proposed method incrementally updates the projective direction for dimension reduction by using the information of a new incoming sample. The experimental results demonstrate that the proposed method is more efficient compared with previously proposed incremental dimension reduction methods.

Estimation Techniques for Three-Dimensional Target Location Based on Linear Least Squared Error Algorithm (선형 최소제곱오차 알고리즘을 응용한 3차원 표적 위치 추정 기법)

  • Han, Jeong Jae;Jung, Yoonhwan;Noh, Sanguk;Park, So Ryoung;Kang, Dokeun;Choi, Wonkyu
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.7
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    • pp.715-722
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    • 2016
  • In this paper, by applying the linear least squared error algorithm, we derive an estimation technique for three dimensional target location when a number of radars are used in detecting a target. The proposed technique is then enhanced by combining GPS information and by assigning variable weights to information sources. The enhanced performance of proposed techniques is confirmed via simulation. It is also observed from simulation results that the performance is robust to the uncertainty of information.

Propagation Factor Based Elevation Estimation Algorithm Selection Method in Multipath Situation (다중경로 상황에서의 전파 인자 기반 고각 추정 알고리즘 선택기법)

  • Daihyun Kwon
    • Journal of Advanced Navigation Technology
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    • v.28 no.2
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    • pp.172-177
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    • 2024
  • This paper presents a method to overcome the problem of increasing elevation estimation error when estimating elevation in a multipath situation with radar. A multipath situation means that radar reception signals reflected from the same target come from multiple paths. In non-multipath, the monopulse method is accurate. For the opposite case, the least square error method is accurate. In multipath situation and when the elevation angle is very low, a singular occurs where the least square error estimate diverges. This singular was identified based on the propagation factor, and monopulse and least square error estimation methods were selectively used. As a result, we succeeded in increasing the accuracy of elevation estimation. MATLAB simulations were performed to verify the method proposed in this paper.

Vocal separation method using weighted β-order minimum mean square error estimation based on kernel back-fitting (커널 백피팅 알고리즘 기반의 가중 β-지수승 최소평균제곱오차 추정방식을 적용한 보컬음 분리 기법)

  • Cho, Hye-Seung;Kim, Hyoung-Gook
    • The Journal of the Acoustical Society of Korea
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    • v.35 no.1
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    • pp.49-54
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    • 2016
  • In this paper, we propose a vocal separation method using weighted ${\beta}$-order minimum mean wquare error estimation (WbE) based on kernel back-fitting algorithm. In spoken speech enhancement, it is well-known that the WbE outperforms the existing Bayesian estimators such as the minimum mean square error (MMSE) of the short-time spectral amplitude (STSA) and the MMSE of the logarithm of the STSA (LSA), in terms of both objective and subjective measures. In the proposed method, WbE is applied to a basic iterative kernel back-fitting algorithm for improving the vocal separation performance from monaural music signal. The experimental results show that the proposed method achieves better separation performance than other existing methods.

Efficient Localization Algorithm for Non-Linear Least Square Estimation (비선형적 최소제곱법을 위한 효율적인 위치추정기법)

  • Lee, Jung-Kyu;Kim, YoungJoon;Kim, Seong-Cheol
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.1
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    • pp.88-95
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    • 2015
  • This paper presents the study of the efficient localization algorithm for non-linear least square estimation. Although non-linear least square(NLS) estimation algorithms are more accurate algorithms than linear least square(LLS) estimation, NLS algorithms have more computation loads because of iterations. This study proposed the efficient algorithm which reduced complexity for small accuracy loss in NLS estimation. Simulation results show the accuracy and complexity of the localization system compared to the proposed algorithm and conventional schemes.

Study on the Transmit Power, MMSE Receiver Filter, and Access Point Selection Optimization Algorithm

  • Oh, Changyoon
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.9
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    • pp.65-72
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    • 2021
  • We consider the joint optimization problem of transmit power level, MMSE receiver filter and access point(AP) selection for multi access points environment. In the previous work, transmit power and MMSE receiver filter were jointly optimized[1] and transmit power and best access point were optimized jointly[2]. For each case, the algorithm was proposed and its convergence which guarantees the minimum total transmit power was proved. In this paper, we further improve the algorithm by jointly optimizing three parameters. More specifically, 1) we propose the algorithm by considering transmit power, MMSE receiver filter and access point selection jointly. 2) we prove that the proposed algorithm guarantees convergence with minimum transmit power consumption. In the simulation results, it is shown that proposed algorithm outperforms two other algorithms, i.e., 1) algorithm with transmit power and MMSE receiver filter, and 2) algorithm with transmit power and best access point selection.

A Study on the Performance Enhancement of Blind Equalizer for CATV Receiver Using the Variable Step Size Algorithm (가변 스텝 크기 알고리즘을 이용한 CATV 수신기용 블라인드 등화기의 성능 향상에 관한 연구)

  • Lee, Hyeon-Cheol;Jo, Il-Jun;Jin, Hyeon-Su;Kim, Seong-Hwan
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.6
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    • pp.33-40
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    • 1996
  • In this paper, we resolved a trade-off problem of the blind equalizer based on the stop-and-go algorithm that is commonly used for QAM demodulation in CATV receiver. The stop-and-go algorithm has used the LMS(least mean square) algorithm in the updating operation of tap weights so that the structure of equalizer is simple, but there is a trade-off between convergence speed and steady state error as in the typical LMS algorithm. We used the variable step size algrithm to improve the convergence speed with the steady state error in the constant level. With respect to the same level of the steady state error, the variable step size stop-and-go algortihm improved convergence speed by about $36%{\sim}56%$ as compared with that of the constant step size algortihm.

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A Study on Least Mean Fourth (LMF) and Least Mean Squares-Fourth (LMSF) Blind Equalization Algorithm (최소평균 사제곱 (LMF) 및 최소평균 제곱과 사제곱을 혼합한 형태 (LMSF)의 블라인드 등화 알고리즘에 관한 연구)

  • Yoon, Tae-Sung;Byun, Youn-Shik
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.3
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    • pp.38-44
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    • 1997
  • In this study, wer derived LMF-Sato, LMSF-Sato complex blind equalization algorithms for complex data. And then, the convergence rates, the convergence characteristics at the steady state and the stability of the proposed LMF and LMSF blind equalization algorithms are compared with those of LMS-Sato blind equalization algorithm. In simulations with 16-QAM data, LMF-Sato and LMSF-Sato algorithms showed better performance comparing with LMS-Sato algorithm generally. When the initial estimation errors of the weights of the equalizer are large, LMF-Sato algorithm showed ill characteristic in stability. However, LMSF-Sato algorithm has good covergence characteristics and preserves robustness.

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