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Adaptive%20IIR%20Filter

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Autoregressive Moving-Average (ARMA) present and past inputs. and past outputs. IIR Filter ... Difference equation of ARMA model. y(n) = ai(n)u(n-i) bi(n)y ... – PowerPoint PPT presentation

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Title: Adaptive%20IIR%20Filter


1
Adaptive IIR Filter
  • Terry Lee
  • EE 491D
  • May 13, 2005

2
Outline
  • Linear Filters FIR IIR
  • Least-mean-square algorithm
  • Adaptive IIR using
  • Output Error Method
  • Equation Error Method
  • Simulations
  • Applications

3
Linear Filters
  • FIR Filter
  • Moving-Average (MA)
  • present and past inputs

IIR Filter Autoregressive Moving-Average
(ARMA) present and past inputs and past outputs
4
IIR Filter
  • Difference equation of ARMA model
  • y(n) ? ai(n)u(n-i) ? bi(n)y(n-i)

M
N
i0
i1
Forward filter
Backwards filter
5
Least-Mean-Square (LMS) Algorithm
  • Linear adaptive filtering algorithm
  • Differs from steepest descent
  • Widely used for its simplicity
  • Consists of
  • 1) A filtering process
  • (mainly FIR model)
  • 2) An adaptive process

6
Least-Mean-Square (LMS) Algorithm
  • Following the steepest descent algorithm,
  • with an unknown environment
  • Tap-input vector u(n)
  • Tap-weight vector w(n)
  • Estimation error e(n)
  • Cost function J(n)e(n)
  • Gradient vector J(n)
  • Update tap-weight vector w(n1)

?
7
Summary of (LMS) Algorithm
  • Parameters M of taps (length of
    filter)
  • µ step-size parameter
  • Filter output is y(n) wH(n)u(n)
  • Error signal is e(n) d(n) y(n)
  • Tap-weight vector w(n1) w(n) µu(n)e(n)

8
Important Factors of an Algorithm
  • Rate of convergence
  • Misadjustment
  • Tracking
  • Robustness
  • Computational Requirements
  • Structure

9
Adaptive IIR Filter
  • Motivation
  • To build the adaptive process around a linear
    IIR filter with fewer number of adjustable
    coefficients than an FIR filter to achieve a
    desired response.

10
Adaptive IIR Filter
  • Two approaches
  • Output error method
  • Equation error method

11
Output Error Method
12
Equation Error Method
  • y(n) ? ai(n)u(n-i) ? bi(n)d(n-i)

M
N
i0
i1
13
Output Error and Equation Error
  • IIR has problems!
  • possible instability
  • slow convergence
  • local minima

14
Simulation
LMS adaptive FIR filter for equalization
15
Simulation
LMS adaptive FIR filter for equalization
16
Simulation
LMS adaptive FIR filter for equalization
17
Applications of IIR
  • acoustic echo cancellation
  • linear prediction
  • adaptive notch filtering
  • adaptive differential pulse code
  • modulation
  • adaptive array processing
  • channel equalization

18
Adaptive Equalizer
  • Telephone channels
  • Fading radio channels
  • Bandwidth-limited channels
  • Removes ISI
  • Recovers information

19
Decision-Feedback Equalizer
(Most popular adaptive IIR equalizer)
20
IIR vs. FIR
  • IIR has slower convergence rate
  • IIR is UNSTABLE
  • IIR introduces more complex structures
  • TRADEOFF
  • IIR uses less coefficients than FIR
  • computationally cheaper
  • able to implement more complex filters

21
Summary
  • Linear Filters FIR IIR
  • Least-mean-square algorithm
  • Adaptive IIR using
  • Output Error Method
  • Equation Error Method
  • Simulations
  • Applications
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