• Title/Summary/Keyword: LMS알고리즘

Search Result 359, Processing Time 0.028 seconds

Improved Sigma Delta Modualtor Based On LMS Algorithm (LMS 알고리즘을 이용한 Sigma Delta Modulator)

  • 신원화;한건희;강성호;이철희
    • Proceedings of the IEEK Conference
    • /
    • 2000.06e
    • /
    • pp.81-84
    • /
    • 2000
  • This paper proposes a new sigma delta modulator structure based on a LMS(Least Mean Square) algorithm that minimizes the quantization noise. The proposed architecture provides 40dB SNR improvement and 35dB wider dynamic range over conventional sigma delta modulation. The proposed architecture provides superior performance especially when the input signal is small.

  • PDF

Intelligent Adaptive Active Noise Control in Non-stationary Noise Environments (비정상 잡음환경에서의 지능형 적응 능동소음제어)

  • Mu, Xiangbin;Ko, JinSeok;Rheem, JaeYeol
    • The Journal of the Acoustical Society of Korea
    • /
    • v.32 no.5
    • /
    • pp.408-414
    • /
    • 2013
  • The famous filtered-x least mean square (FxLMS) algorithm for active noise control (ANC) systems may become unstable in non-stationary noise environment. To solve this problem, Sun's algorithm and Akhtar's algorithm are developed based on modifying the reference signal in update of FxLMS algorithm, but these two algorithms have dissatisfactory stability in dealing with sustaining impulsive noise. In proposed algorithm, probability estimation and zero-crossing rate (ZCR) control are used to improve the stability and performance, at the same time, an optimal parameter selection based on fuzzy system is utilized. Computer simulation results prove the proposed algorithm has faster convergence and better stability in non-stationary noise environment.

Channel Estimation Based on LMS Algorithm for MIMO-OFDM System (MIMO-OFDM을 위한 LMS 알고리즘 기반의 채널추정)

  • Hwang, Suk-Seung
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.7 no.6
    • /
    • pp.1455-1461
    • /
    • 2012
  • MIMO-OFDM which is one of core techniques for the high-speed mobile communication system requires the efficient channel estimation method with low estimation error and computational complexity, for accurately receiving data. In this paper, we propose a channel estimation algorithm with low channel estimation error comparing with LS which is primarily employed to the MIMO-OFDM system, and with low computational complexity comparing with MMSE. The proposed algorithm estimates channel vectors based on the LMS adaptive algorithm in the time domain, and the estimated channel vector is sent to the detector after FFT. We also suggest a preamble architecture for the proposed MIMO-OFDM channel estimation algorithm. The computer simulation example is provided to illustrate the performance of the proposed algorithm.

An Improvement of the Convergence Speed through Tap Weight Updating of Dta-Recycling LMS Algorithm (데이터 재순환 LMS알고리즘의 탭 가중치 갱신을 통한 수렴속도 개선)

  • 김원균;김광준;나상동
    • Proceedings of the Korean Information Science Society Conference
    • /
    • 1998.10a
    • /
    • pp.624-626
    • /
    • 1998
  • In this paper. a new simple and efficient technique to improve the convergence speed of LMS algorithm is introduced. The convergence characteristics of the proposed algorithm, whose coefficients are multiply adapted in a symbol time period by recycling the received data, are analysis to prove theoretically the improvement of convergence speed. The theoretical analysis shows that the data-recycling LMS technique can increase convergence speed by (B+1) times, where B is the number of recycled data. The results of the computer simulation demonstrate that the simulation results are in accordance with the theoretical analysis and the superiority of the filter algorithm

  • PDF

Speaker Verification Using Hidden LMS Adaptive Filtering Algorithm and Competitive Learning Neural Network (Hidden LMS 적응 필터링 알고리즘을 이용한 경쟁학습 화자검증)

  • Cho, Seong-Won;Kim, Jae-Min
    • The Transactions of the Korean Institute of Electrical Engineers D
    • /
    • v.51 no.2
    • /
    • pp.69-77
    • /
    • 2002
  • Speaker verification can be classified in two categories, text-dependent speaker verification and text-independent speaker verification. In this paper, we discuss text-dependent speaker verification. Text-dependent speaker verification system determines whether the sound characteristics of the speaker are equal to those of the specific person or not. In this paper we obtain the speaker data using a sound card in various noisy conditions, apply a new Hidden LMS (Least Mean Square) adaptive algorithm to it, and extract LPC (Linear Predictive Coding)-cepstrum coefficients as feature vectors. Finally, we use a competitive learning neural network for speaker verification. The proposed hidden LMS adaptive filter using a neural network reduces noise and enhances features in various noisy conditions. We construct a separate neural network for each speaker, which makes it unnecessary to train the whole network for a new added speaker and makes the system expansion easy. We experimentally prove that the proposed method improves the speaker verification performance.

A New LMS Algorithm for Improved Convergence Time in Active Noise Control (수렴속도 개선을 위한 새로운 LMS 알고리즘)

  • Park, Kyoung-Ho;Kim, Il-Hwan
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.7 no.3
    • /
    • pp.276-279
    • /
    • 2001
  • Many industrial processes that are operated by rotating machines and large air-moving fans are excellent examples to which the single channel ANC systems can be applied. In these environments, the active noise control techniques are most popular nowadays. In this paper, a modified LMS algorithm(EAC, Error Amplitude Compared) is proposed. The algorithm is a kind of variable step-size LMS-type algorithm. Computer simulations show that the proposed EAC algorithm achieves a better convergence time than a conventional VS(Variable Step-Size) algorithm, Also, this algorithm has been implemented by using and experimental duct system.

  • PDF

A Study on Prediction method for Forward link ACM of Satellite Communication Public Testbed via COMS (천리안 위성을 이용한 위성통신 공공 테스트베드 포워드링크 ACM 구축을 위한 예측기법 연구)

  • Ryu, Joon-Gyu;Hong, Sung-Yong
    • Journal of Satellite, Information and Communications
    • /
    • v.7 no.1
    • /
    • pp.82-85
    • /
    • 2012
  • In this paper, we present the forward link ACM method to improve the link availability and system throughput. Also, we compare the prediction algorithm between slope based prediction and LMS algorithm. The simulation results show that the 99% of predicted values in LMS algorithm is within 3dB and that of predicted values in the slope based prediction method is within 4.5dB.

Active noise control using fuzzy LMS algorithm in ducts (퍼지 LMS 알고리즘을 이용한 덕트의 능동소음제어)

  • Ahn, Dong-Jun;Kim, Kyun-Tae;Nam, Hyun-Do
    • Proceedings of the KIEE Conference
    • /
    • 1994.11a
    • /
    • pp.373-375
    • /
    • 1994
  • In this paper, the fuzzy LMS algorithm where the convergence coefficient is computed by a fuzzy logic controller was proposed. The proposed fuzzy LMS algorithm showed better convergence property and stability than conventional LMS algorithms. The estimation error and misadaptation degree were used for Input of the fuzzy logic controller. In a airconditioning duct case, various conditions were investigated to design active noise controllers. A case with acoustic feedback, the proposed algorithm showed good performances through computer simulations.

  • PDF

A Robust Error Adaptive NLMS Algorithm for Echo Cancellations of Communication Systems (통신망의 반향제거를 위한 강인한 오차적응 NLMS 알고리즘)

  • Kim, Min-Soo;Chung, Chan-Soo
    • Proceedings of the KIEE Conference
    • /
    • 2005.07d
    • /
    • pp.2995-2997
    • /
    • 2005
  • 통신망에서 최적 적응 반향제거기(Echo Canceller; EC)는 반향성분이 길게 존재하는 환경에서도 실시간으로 동작할 수 있도록 알고리즘이 간결하여야 하며, 시간에 따라 빠르게 변하는 동특성의 반향경로에서도 동작을 보장할 수 있도록 빠른 수렴특성을 갖아야 한다. 또한, 전화망에서 수십 [ms] 이상의 지연이 발생 할 경우에도 반향제거 성능이 우수해야 한다. 본 논문에서는 이러한 조건을 만족시키기 위해 오차의 크기에 따라 수렴속도를 가변시키는 오차적응 NLMS(Error-Adaptive NLMS) 알고리즘을 제안하였으며, 시뮬레이션을 통해 일반적으로 사용되는 LMS(Least Mean Square) 알고리즘과 이를 개선한 NLMS(Normalized LMS) 알고리즘과 성능을 비교하였다.

  • PDF