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Efficient implementation of error-feedback LSL algorithm

Efficient implementation of error-feedback LSL algorithm

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An error feedback LSL algorithm is presented which has a reduced computational complexity and makes use of both a priori and a posteriori prediction errors. A simple numerical convention is proposed to assure numerical stability for poor persistent excitation. Simulation results illustrate that divisions can be implemented with reduced wordlength without leading to a significant decrease in the overall accuracy even in floating-point implementations. This fact allows the use of lookup tables for implementing divisions. Moreover, the proposed algorithm has an inherent parallelism that can be advantageously exploited for fast implementations.

Inspec keywords: filtering theory; adaptive filters; signal processing; errors; least squares approximations; echo suppression; table lookup; feedback; parallel algorithms; computational complexity; numerical stability

Other keywords: numerical stability; prediction errors; wordlength reduction; computational complexity reduction; lookup tables; real-time adaptive filtering; least squares lattice algorithm; error-feedback LSL algorithm; fast implementations; acoustic echo cancellation

Subjects: Interpolation and function approximation (numerical analysis); Digital signal processing; Interpolation and function approximation (numerical analysis); Parallel programming and algorithm theory; Filtering methods in signal processing; Signal processing theory

References

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      • Miranda, M.D., Gerken, M.: `Performance of the a priori and a posteriori QR-LSL algorithms in a limitedprecision environment', Proc. ICASSP97, April 1997, Munique, p. 2337–2340.
    2. 2)
      • F. Ling , D. Manolakis , J.G. Proakis . Numerically robust least-squares lattice-ladder algorithms with directupdating of the reflection coefficients. IEEE Trans. , 4 , 837 - 845
    3. 3)
      • A. Gilloire , E. Moulines , D. Slock , P. Duhamel , A.R. Figueiras-Vidal . (1996) State of the art in acoustic echo cancellation, Digital signal processing in telecommunications.
    4. 4)
      • P.A. Regalia . Numerical stability properties of a QR-based fast least squares algorithm. IEEE Trans. , 6 , 2096 - 2109
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      • S. Haykin . (1996) Adaptive filter theory.
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