论文信息 - A general method of minimum cross-entropy spectral estimation

A general method of minimum cross-entropy spectral estimation

A new, general approach to estimating power spectra is presented, based on minimizing a cross-entropy functional involving spectral densities. Examples are worked out using this approach as well as Shore's [5] minimum cross-entropy spectral analysis (MCESA) and Burg's [7] maximum entropy spectral analysis (MESA). The results show that aside from its wider applicability, ease of implementation, and pedagogical advantage, the method performs better than MESA and equally well or better than MCESA.

[1] S. Gull,et al. Image reconstruction from incomplete and noisy data , 1978, Nature.

[2] A. Papoulis,et al. Random modulation: A review , 1983 .

[3] E. Jaynes. Information Theory and Statistical Mechanics , 1957 .

[4] A NEW APPROACH TO THE ESTIMATION OF CONTINUOUS SPECTRA , 1981 .

[5] D. Middleton. An Introduction to Statistical Communication Theory , 1960 .

[6] Athanasios Papoulis,et al. Probability, Random Variables and Stochastic Processes , 1965 .

[7] J. P. Burg,et al. Maximum entropy spectral analysis. , 1967 .

[8] J. Shore. Minimum cross-entropy spectral analysis , 1981 .

[9] Rodney W. Johnson,et al. Axiomatic derivation of the principle of maximum entropy and the principle of minimum cross-entropy , 1980, IEEE Trans. Inf. Theory.

[10] Nai-Long Wu. An explicit solution and data extension in the maximum entropy method , 1983 .

[11] Bruno O. Shubert,et al. Random variables and stochastic processes , 1979 .

[12] Graham A. Jullien,et al. Implementation of FFT Structures Using the Residue Number System , 1979, IEEE Transactions on Computers.

[13] Peyton Z. Peebles. Communication System Principles , 1976 .

[14] B. Frieden. Restoring with maximum likelihood and maximum entropy. , 1972, Journal of the Optical Society of America.