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- Sundar G. Sankaran, A. A. Beex
- IEEE Trans. Signal Processing
- 2000

Over the last decade, a class of equivalent algorithms that accelerate the convergence of the normalized LMS (NLMS) algorithm, especially for colored inputs, has been discovered independently. The affine projection algorithm (APA) is the earliest and most popular algorithm in this class that inherits its name. The usual APA algorithms update weight… (More)

(ABSTRACT) Adaptive filtering techniques are used in a wide range of applications, including echo cancellation, adaptive equalization, adaptive noise cancellation, and adaptive beamforming. The performance of an adaptive filtering algorithm is evaluated based on its convergence rate, misadjustment, computational requirements, and numerical robustness. We… (More)

- Sundar G. Sankaran, A. A. Beex
- 2002 IEEE International Conference on Acoustics…
- 2002

We present the tracking properties of the Normalized LMS and affine projection class of algorithms for a randomly time-varying system under certain simplifying assumptions on the data. An expression is given for the steady-state mean-squared error. The dependence of the steady-state error and of the tracking properties on three user-selectable parameters,… (More)

- Sundar G. Sankaran, Brian J. Zargari, +25 authors Bruce A. Wooley
- IEEE Communications Magazine
- 2009

- Sundar G. Sankaran, A. A. Beex
- ISCAS
- 1999

A stereophonic echo canceler is proposed based on the Normalized LMS algorithm with orthogonal correction factors (NLMS-OCF). The echo canceler is modeled using a two-input single-output finite-impulse-response (FIR) structure. NLMSOCF updates the echo canceler coefficients based on multiple input vectors, while NLMS adapts the coefficients based on a… (More)

- Sundar G. Sankaran, A. A. Beex
- ICASSP
- 1999

Balanced realizations are attractive for adaptive filtering, due to their minimum parameter sensitivity and due to their usefulness in model-reduction problems. A balanced-realization based adaptive IIR filtering algorithm is presented. The proposed algorithm uses a stochastic-gradient based search technique to minimize the output error. The algorithm… (More)

- Sundar G. Sankaran, A. A. Beex
- ICASSP
- 1998

We modify the off-line system identification procedure proposed by Regalia [4] into an adaptive IIR filtering algorithm based on the stochastic gradient method. The proposed algorithm aims to minimize equation error, recursively, under a unit-norm constraint on the characteristic polynomial instead of the usual monic constraint. The unit-norm constraint… (More)

- Sundar G. Sankaran, A. A. Beex
- IEEE Signal Processing Letters
- 1999

The bias problem associated with equation error based adaptive infinite impulse response (IIR) filtering can be surmounted by imposing a unit-norm constraint on the autoregressive (AR) coefficients. We propose a hyperspherical parameterization to convert the unit-norm-constrained optimization into an unconstrained optimization. We show that the… (More)

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