### Abstract

Several new two-dimensional adaptive infinite-impulse response (IIR) filtering algorithms are derived and simulated. These new algorithms are based upon the one-dimensional version of the algorithm developed by Fan and Jenkins [3]. This algorithm was shown to experimentally possess the ability to converge to the global minimum of the mean square error (MSE) even in cases where the mean square error (MSE) surface is ill-conditioned. In addition, further enhancements to this new algorithm were made to improve convergence rate performance. An estimate of the Hessian is incorporated into the adaptive filter coefficient update expressions. Least Mean Square (LMS), Recursive Least Square (RLS), Gauss-Newton (GN), and Fast Quasi-Newton (FQN) forms of the two-dimensional Fan-Jenkins algorithm are formulated and compared via simulation for several examples.

Original language | English (US) |
---|---|

Pages (from-to) | 703-706 |

Number of pages | 4 |

Journal | Proceedings - IEEE International Symposium on Circuits and Systems |

Volume | 2 |

State | Published - 1996 |

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### All Science Journal Classification (ASJC) codes

- Electrical and Electronic Engineering
- Electronic, Optical and Magnetic Materials

### Cite this

*Proceedings - IEEE International Symposium on Circuits and Systems*,

*2*, 703-706.

}

*Proceedings - IEEE International Symposium on Circuits and Systems*, vol. 2, pp. 703-706.

**Fast two-dimensional adaptive IIR algorithms.** / Soni, Robert A.; Jenkins, W. Kenneth.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Fast two-dimensional adaptive IIR algorithms

AU - Soni, Robert A.

AU - Jenkins, W. Kenneth

PY - 1996

Y1 - 1996

N2 - Several new two-dimensional adaptive infinite-impulse response (IIR) filtering algorithms are derived and simulated. These new algorithms are based upon the one-dimensional version of the algorithm developed by Fan and Jenkins [3]. This algorithm was shown to experimentally possess the ability to converge to the global minimum of the mean square error (MSE) even in cases where the mean square error (MSE) surface is ill-conditioned. In addition, further enhancements to this new algorithm were made to improve convergence rate performance. An estimate of the Hessian is incorporated into the adaptive filter coefficient update expressions. Least Mean Square (LMS), Recursive Least Square (RLS), Gauss-Newton (GN), and Fast Quasi-Newton (FQN) forms of the two-dimensional Fan-Jenkins algorithm are formulated and compared via simulation for several examples.

AB - Several new two-dimensional adaptive infinite-impulse response (IIR) filtering algorithms are derived and simulated. These new algorithms are based upon the one-dimensional version of the algorithm developed by Fan and Jenkins [3]. This algorithm was shown to experimentally possess the ability to converge to the global minimum of the mean square error (MSE) even in cases where the mean square error (MSE) surface is ill-conditioned. In addition, further enhancements to this new algorithm were made to improve convergence rate performance. An estimate of the Hessian is incorporated into the adaptive filter coefficient update expressions. Least Mean Square (LMS), Recursive Least Square (RLS), Gauss-Newton (GN), and Fast Quasi-Newton (FQN) forms of the two-dimensional Fan-Jenkins algorithm are formulated and compared via simulation for several examples.

UR - http://www.scopus.com/inward/record.url?scp=0029712295&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0029712295&partnerID=8YFLogxK

M3 - Article

VL - 2

SP - 703

EP - 706

JO - Proceedings - IEEE International Symposium on Circuits and Systems

JF - Proceedings - IEEE International Symposium on Circuits and Systems

SN - 0271-4310

ER -