Reduced complexity recursive least square lattice structure adaptive filter by means of estimating the backward and forward error prediction squares using binomial expansion
AssigneeMotorola, Inc.
InventorsDavid L. Barron, James B. Piket, Daniel Rokusek
Life of this patent
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Abstract
A method for reducing a computational complexity of an m-stage adaptive filter is provided by expanding a weighted sum of forward prediction error squares into a corresponding binomial expansion series, expanding a weighted sum of backward prediction error squares into a corresponding binomial expansion series, and determining coefficient updates of the adaptive filter with the weighted sums of forward and backward prediction error squares approximated by a select number of terms of their corresponding binomial expansion series.
Claims9
A method for reducing computational complexity of an m-stage adaptive filter, the method comprising:
- receiving an input signal-to be filtered;
- developing a set of filter coefficients for the received input signal;
- expanding a weighted sum of forward prediction error squares into a corresponding binomial expansion series;
- expanding a weighted sum of backward prediction error squares into a corresponding binomial expansion series;
- determining coefficient updates of the adaptive filter with the weighted sum of forward and backward prediction error squares approximated by a select number of terms of their corresponding binomial expansion series;
- filtering the received input signal in accordance with the updated coefficients to produce a filtered signal;
- and
- providing the filtered signal as an output signal.
A method for an m-stage recursive least squares lattice structure adaptive filter, the method comprising:
- receiving an input signal to be filtered at an input of the adaptive filter;
- developing a set of filter coefficients for the received input signal;
- updating the set of filter coefficients by estimating an expansion of Taylor's theorem within a given region of convergence;
- filtering the input signal using the updated set of filter coefficients;
- and
- producing a filtered signal at an output of the adaptive filter.
An adaptive filter comprising:
- an interface to receive an input signal;
- a processor operative in conjunction with stored data and instructions to recursively update filter coefficients for each stage of the adaptive filter while producing a filtered signal, the processor configured to updating the set of filter coefficients by estimating an expansion of Taylor's theorem within a given region of convergence;
- and
- an interface to provide the filtered signal as an output signal.
Dependencies are inferred from the claim text.