Time average estimation in the fraction-of-time probability framework

@article{Dehay2018TimeAE,
  title={Time average estimation in the fraction-of-time probability framework},
  author={Dominique Dehay and Jacek Leskow and Antonio Napolitano},
  journal={Signal Process.},
  year={2018},
  volume={153},
  pages={275-290}
}
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References

SHOWING 1-10 OF 47 REFERENCES

Central Limit Theorem in the Functional Approach

TLDR
The central limit theorem is proved within the framework of the functional approach for signal analysis, showing that if a sequence of independent signals fulfills some mild regularity assumptions, then the asymptotic distribution of the appropriately scaled average of such signals has a limiting normal distribution.

Fraction-of-time probability for time-series that exhibit cyclostationarity

Subsampling for continuous-time almost periodically correlated processes

Statistical spectral analysis : a nonprobabilistic theory

This book presents a general theory and methodology for empirical spectral analysis. The treatment is original because it does not make use of the difficult concept of ergodicity to provide a link…

The cumulant theory of cyclostationary time-series. I. Foundation

TLDR
It is established that the temporal and spectral cumulants have certain mathematical and practical advantages over their moment counterparts.

The cumulant theory of cyclostationary time-series. II. Development and applications

TLDR
The development of the theory of nonlinear processing of cyclostationary time-series that is initiated in Part I is continued and a new type of cumulant for complex-valued variables is introduced and used to generalize the temporal and spectral moments and cumulants for cyclostators from real-valued tocomplex-valued time- series.

Empirical determination of the frequencies of an almost periodic time series

This article deals with the problem of the determination of the finite or countable set of frequencies belonging to any arbitrary almost periodic (in the sense of Bohr) time series. For this purpose,…

Optimal experiment design for identification of ARX models with constrained output in non-Gaussian noise

Stationary sequences and random fields

I Stationary Processes.- 1. General Discussion.- 2. Positive Definite Functions.- 3. Fourier Representation of a Weakly Stationary Process.- Problems.- Notes.- II Prediction and Moments.- 1.…

Functional limit theory for the spectral covariance estimator

Processes that exhibit repeatability in their kth-order moments are frequently studied in signal analysis. Such repeatability can be conveniently expressed with the help of almost periodicity. In…