WO2007001787A3 - A reduced complexity recursive least square lattice structure adaptive filter by means of approximating the forward error prediction squares using the backward error prediction squares - Google Patents

A reduced complexity recursive least square lattice structure adaptive filter by means of approximating the forward error prediction squares using the backward error prediction squares Download PDF

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Publication number
WO2007001787A3
WO2007001787A3 PCT/US2006/022289 US2006022289W WO2007001787A3 WO 2007001787 A3 WO2007001787 A3 WO 2007001787A3 US 2006022289 W US2006022289 W US 2006022289W WO 2007001787 A3 WO2007001787 A3 WO 2007001787A3
Authority
WO
WIPO (PCT)
Prior art keywords
error prediction
prediction squares
approximating
squares
adaptive filter
Prior art date
Application number
PCT/US2006/022289
Other languages
French (fr)
Other versions
WO2007001787A2 (en
Inventor
David L Barron
James B Piket
Christopher W Springfield
Original Assignee
Motorola Inc
David L Barron
James B Piket
Christopher W Springfield
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US11/399,989 external-priority patent/US20060288067A1/en
Application filed by Motorola Inc, David L Barron, James B Piket, Christopher W Springfield filed Critical Motorola Inc
Publication of WO2007001787A2 publication Critical patent/WO2007001787A2/en
Publication of WO2007001787A3 publication Critical patent/WO2007001787A3/en

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Classifications

    • HELECTRICITY
    • H03ELECTRONIC CIRCUITRY
    • H03HIMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
    • H03H21/00Adaptive networks
    • H03H21/0012Digital adaptive filters
    • H03H21/0014Lattice filters
    • HELECTRICITY
    • H03ELECTRONIC CIRCUITRY
    • H03HIMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
    • H03H21/00Adaptive networks
    • H03H21/0012Digital adaptive filters
    • H03H21/0043Adaptive algorithms
    • H03H2021/0049Recursive least squares algorithm

Abstract

A method for reducing a computational complexity of an m-stage adaptive filter is provided by determining a weighted sum of backward prediction error squares for stage m at time n, determining a conversion factor for stage m at time n, inverting the weighted sum of backward prediction error squares, and approximating a weighted sum of forward prediction error squares by combining the inverted weighted sum of backward prediction error squares with the conversion factor.
PCT/US2006/022289 2005-06-20 2006-06-08 A reduced complexity recursive least square lattice structure adaptive filter by means of approximating the forward error prediction squares using the backward error prediction squares WO2007001787A2 (en)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US69234505P 2005-06-20 2005-06-20
US60/692,345 2005-06-20
US11/399,989 US20060288067A1 (en) 2005-06-20 2006-04-07 Reduced complexity recursive least square lattice structure adaptive filter by means of approximating the forward error prediction squares using the backward error prediction squares
US11/399,989 2006-04-07

Publications (2)

Publication Number Publication Date
WO2007001787A2 WO2007001787A2 (en) 2007-01-04
WO2007001787A3 true WO2007001787A3 (en) 2007-07-12

Family

ID=37595658

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2006/022289 WO2007001787A2 (en) 2005-06-20 2006-06-08 A reduced complexity recursive least square lattice structure adaptive filter by means of approximating the forward error prediction squares using the backward error prediction squares

Country Status (1)

Country Link
WO (1) WO2007001787A2 (en)

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
CIOFFI J.: "The Fast Householder Filters RLS Adaptive Filter", IEEE, 1990, pages 1619 - 1622, XP010641823 *

Also Published As

Publication number Publication date
WO2007001787A2 (en) 2007-01-04

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