• Title/Summary/Keyword: Noise estimation

Search Result 1,983, Processing Time 0.027 seconds

RLS Adaptive IIR Filters Based on Equation Error Methods Considering Additive Noises

  • Muneyasu, Mitsuji;Kamikawa, Hidefumi;Hinamoto, Takao
    • Proceedings of the IEEK Conference
    • /
    • 2000.07a
    • /
    • pp.215-218
    • /
    • 2000

  • In this paper, a new algorithm for adaptive IIR filters based on equation error methods using the RLS algorithm is proposed. In the proposed algorithm, the concept of feedback of the scaled output error proposed by tin and Unbehauen is employed and the forgetting factor is varied in adaptation process for avoiding the accumulation of the estimation error for additive noise . The proposed algorithm has the good convergence property without the parameter estimation error under the existence of mea-surement noise.

  • PDF

Hybrid Noise Reduction Algorithm Using Wavelet Transform (웨이블릿 변환을 이용한 하이브리드 방식의 잡음 제거 알고리즘)

  • Seo, Young-Ho;Kim, Dong-Wook
    • Proceedings of the IEEK Conference
    • /
    • 2007.07a
    • /
    • pp.367-368
    • /
    • 2007

  • In this paper, we propose a new de-noising algorithm for 2 dimensional image using discrete wavelet transform. The proposed algorithm consists of edge detection in spatial domain, zero-tree estimation, subband estimation, and shrinkage algorithm. The results from it shows that the denoised image which Is damaged by 20% gaussian noise has 28dB quality for the original one.

  • PDF

A Practical Real-Time LOS Rate Estimator with Time-Varying Measurement Noise Variance (시변 측정잡음 모델을 고려한 실시간 시선각 변화율 추정필터)

  • Na, Won-Sang;Lee, Jin-Ik
    • Proceedings of the KIEE Conference
    • /
    • 2003.07d
    • /
    • pp.2082-2084
    • /
    • 2003

  • A practical real-time LOS rate estimator is proposed to handle the time-varying measurement noise statistics. To calculate the optimal Kalman gain, the algebraic transformation method is taken into account. By using the algebraic transformation, the differential algebraic Riccati equation(DARE) regarding estimation error covariance is replaced by the simple algebraic Riccati equation(ARE). The proposed LOS estimation filter gain is only a function of relative range. Consequently, the proposed method is computationally very efficient and suitable for embedded environment.

  • PDF