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Highly Cited

2012

Highly Cited

2012

We address the problem of in-network distributed estimation for sparse vectors. In order to exploit the underlying sparsity of… Expand

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Highly Cited

2010

Highly Cited

2010

This paper presents an efficient adaptive combination strategy for the distributed estimation problem over diffusion networks in… Expand

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Highly Cited

2010

Highly Cited

2010

We consider adaptive system identification problems with convex constraints and propose a family of regularized Least-Mean-Square… Expand

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Highly Cited

2008

Highly Cited

2008

The combination of the famed kernel trick and the least-mean-square (LMS) algorithm provides an interesting sample-by-sample… Expand

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Highly Cited

2008

Highly Cited

2008

This paper studies the statistical behavior of an affine combination of the outputs of two least mean-square (LMS) adaptive… Expand

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Highly Cited

2005

Highly Cited

2005

Frequency is an important parameter in power system monitoring, control, and protection. A least mean square (LMS) algorithm in… Expand

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2005

2005

When the ordinary least squares method is applied to the parameter estimation problem with noisy data matrix, it is well-known… Expand

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Highly Cited

2000

Highly Cited

2000

On typical echo paths, the proportionate normalized least-mean-squares (PNLMS) adaptation algorithm converges significantly… Expand

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Highly Cited

1985

Highly Cited

1985

The Adaptive Least Squares Correlation is a very potent and flexible technique for all kinds of data matching problems. Here its… Expand

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Highly Cited

1984

Highly Cited

1984

New steepest descent algorithms for adaptive filtering and have been devised which allow error minimization in the mean fourth… Expand

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