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T Kailath - One of the best experts on this subject based on the ideXlab platform.

  • modular and numerically stable fast transversal Filters for multichannel and multiexperiment rls
    IEEE Transactions on Signal Processing, 1992
    Co-Authors: Dirk Slock, H Levari, Luigi Chisci, T Kailath
    Abstract:

    The authors present scalar implementations of multichannel and multiexperiment fast recursive least squares algorithms in transversal Filter Form, known as fast transversal Filter (FTF) algorithms. By processing the different channels and/or experiments one at a time, the multichannel and/or multiexperiment algorithm decomposes into a set of intertwined single-channel single-experiment algorithms. For multichannel algorithms, the general case of possibly different Filter orders in different channels is handled. Geometrically, this modular decomposition approach corresponds to a Gram-Schmidt orthogonalization of multiple error vectors. Algebraically, this technique corresponds to matrix triangularization of error covariance matrices and converts matrix operations into a regular set of scalar operations. Modular algorithm structures that are amenable to VLSI implementation on arrays of parallel processors naturally follow from the present approach. Numerically, the resulting algorithm benefits from the advantages of triangularization techniques in block processing. >

Dirk Slock - One of the best experts on this subject based on the ideXlab platform.

  • modular and numerically stable fast transversal Filters for multichannel and multiexperiment rls
    IEEE Transactions on Signal Processing, 1992
    Co-Authors: Dirk Slock, H Levari, Luigi Chisci, T Kailath
    Abstract:

    The authors present scalar implementations of multichannel and multiexperiment fast recursive least squares algorithms in transversal Filter Form, known as fast transversal Filter (FTF) algorithms. By processing the different channels and/or experiments one at a time, the multichannel and/or multiexperiment algorithm decomposes into a set of intertwined single-channel single-experiment algorithms. For multichannel algorithms, the general case of possibly different Filter orders in different channels is handled. Geometrically, this modular decomposition approach corresponds to a Gram-Schmidt orthogonalization of multiple error vectors. Algebraically, this technique corresponds to matrix triangularization of error covariance matrices and converts matrix operations into a regular set of scalar operations. Modular algorithm structures that are amenable to VLSI implementation on arrays of parallel processors naturally follow from the present approach. Numerically, the resulting algorithm benefits from the advantages of triangularization techniques in block processing. >

Luigi Chisci - One of the best experts on this subject based on the ideXlab platform.

  • modular and numerically stable fast transversal Filters for multichannel and multiexperiment rls
    IEEE Transactions on Signal Processing, 1992
    Co-Authors: Dirk Slock, H Levari, Luigi Chisci, T Kailath
    Abstract:

    The authors present scalar implementations of multichannel and multiexperiment fast recursive least squares algorithms in transversal Filter Form, known as fast transversal Filter (FTF) algorithms. By processing the different channels and/or experiments one at a time, the multichannel and/or multiexperiment algorithm decomposes into a set of intertwined single-channel single-experiment algorithms. For multichannel algorithms, the general case of possibly different Filter orders in different channels is handled. Geometrically, this modular decomposition approach corresponds to a Gram-Schmidt orthogonalization of multiple error vectors. Algebraically, this technique corresponds to matrix triangularization of error covariance matrices and converts matrix operations into a regular set of scalar operations. Modular algorithm structures that are amenable to VLSI implementation on arrays of parallel processors naturally follow from the present approach. Numerically, the resulting algorithm benefits from the advantages of triangularization techniques in block processing. >

H Levari - One of the best experts on this subject based on the ideXlab platform.

  • modular and numerically stable fast transversal Filters for multichannel and multiexperiment rls
    IEEE Transactions on Signal Processing, 1992
    Co-Authors: Dirk Slock, H Levari, Luigi Chisci, T Kailath
    Abstract:

    The authors present scalar implementations of multichannel and multiexperiment fast recursive least squares algorithms in transversal Filter Form, known as fast transversal Filter (FTF) algorithms. By processing the different channels and/or experiments one at a time, the multichannel and/or multiexperiment algorithm decomposes into a set of intertwined single-channel single-experiment algorithms. For multichannel algorithms, the general case of possibly different Filter orders in different channels is handled. Geometrically, this modular decomposition approach corresponds to a Gram-Schmidt orthogonalization of multiple error vectors. Algebraically, this technique corresponds to matrix triangularization of error covariance matrices and converts matrix operations into a regular set of scalar operations. Modular algorithm structures that are amenable to VLSI implementation on arrays of parallel processors naturally follow from the present approach. Numerically, the resulting algorithm benefits from the advantages of triangularization techniques in block processing. >

Milos Doroslovacki - One of the best experts on this subject based on the ideXlab platform.

  • Cascade lattice IIR adaptive Filters
    IEEE Transactions on Signal Processing, 1994
    Co-Authors: K.x. Miao, H. Howard Fan, Milos Doroslovacki
    Abstract:

    The feedback lattice Filter Forms, including the two-multiplier Form and the normalized Form, are examined with respect to their relationships to the feedback direct Form Filter. Specifically, the transFormation matrix between the lattice Forms and the direct Form is derived; parameter and state relationships between the lattice Forms and the direct Form are therefore obtained. An IIR Filter structure-the cascade lattice IIR structure-is constructed. Based on this structure, three IIR adaptive Filtering algorithms in the two-multiplier Form can then be developed following the gradient approach, the Steiglitz-McBride approach and the hyperstability approach. Convergence of these algorithms is theoretically analyzed using either the ODE approach or the hyperstability theorem. These algorithms are then simplified into Forms computationally as efficient as their corresponding direct Form algorithms. Relationships of the simplified algorithms to the direct Form algorithms are also studied, which disclose a consistency in algorithm structure regardless of the Filter Form. Three normalized lattice algorithms can also be derived from the two-multiplier lattice algorithms. Experimental results show much improved perFormance of the normalized lattice algorithms over the two-multiplier lattice algorithms and the direct Form algorithms. >