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Partial Differentiation of Real Binary Functions

100%

Xie B., Liang X., Li H.

Formalized Mathematics

2008

tom 16

nr 4

333-338

In this article, we define two single-variable functions SVF1 and SVF2, then discuss partial differentiation of real binary functions by dint of one variable function SVF1 and SVF2. The main properties of partial differentiation are shown [7].MML identifier: PDIFF 2, version: 7.9.03 4.104.1021

An efficient algorithm for estimating the parameters of superimposed exponential signals in multiplicative and additive noise

88%

Bian J., Peng H., Xing J., Liu Z., Li H.

International Journal of Applied Mathematics and Computer Science

2013

tom 23

nr 1

117-129

This paper considers parameter estimation of superimposed exponential signals in multiplicative and additive noise which are all independent and identically distributed. A modified Newton-Raphson algorithm is used to estimate the frequencies of the considered model, which is further used to estimate other linear parameters. It is proved that the modified Newton-Raphson algorithm is robust and the corresponding estimators of frequencies attain the same convergence rate with Least Squares Estimators (LSEs) under the same noise conditions, but it outperforms LSEs in terms of the mean squared errors. Finally, the effectiveness of the algorithm is verified by some numerical experiments.

Ograniczanie wyników

1 Formalized Mathematics

1 International Journal of Applied Mathematics and Computer Science

2 Li H.

1 Bian J.

1 Liang X.

1 Liu Z.

1 Peng H.

1 Xie B.

1 Xing J.

1 2013

1 2008

Wyniki wyszukiwania

Partial Differentiation of Real Binary Functions

An efficient algorithm for estimating the parameters of superimposed exponential signals in multiplicative and additive noise