scholarly journals Higher-Order Information Measures from Cumulative Densities in Continuous Variable Quantum Systems

2020 ◽  
Vol 2 (4) ◽  
pp. 560-578
Author(s):  
Saúl J. C. Salazar ◽  
Humberto G. Laguna ◽  
Robin P. Sagar
Keyword(s):  
Continuous Variable ◽  
Quantum Systems ◽  
Higher Order ◽  
Residual Entropy ◽  
Information Measures ◽  
Cumulative Residual Entropy ◽  
Interacting Systems ◽  
Correlation Measures ◽  
Cumulative Residual ◽  
Definition Of

A definition of three-variable cumulative residual entropy is introduced, and then used to obtain expressions for higher order or triple-wise correlation measures, that are based on cumulative residual densities. These information measures are calculated in continuous variable quantum systems comprised of three oscillators, and their behaviour compared to the analogous measures from Shannon information theory. There is an overall consistency in the behaviour of the newly introduced measures as compared to the Shannon ones. There are, however, differences in interpretation, in the case of three uncoupled oscillators, where the correlation is due to wave function symmetry. In interacting systems, the cumulative based measures are shown in order to detect salient features, which are also present in the Shannon based ones.

Multiscale Fractional Cumulative Residual Entropy of Higher-Order Moments for Estimating Uncertainty

2020 ◽  
Vol 19 (04) ◽  
pp. 2050038
Author(s):  
Keqiang Dong ◽  
Xiaofang Zhang
Keyword(s):  
Time Series ◽  
Logistic Map ◽  
Higher Order ◽  
Stationary Time Series ◽  
Residual Entropy ◽  
Third Order ◽  
Cumulative Residual Entropy ◽  
Cumulative Residual ◽  
Simulated Time ◽  
Analyze Time Series

The fractional cumulative residual entropy is not only a powerful tool for the analysis of complex system, but also a promising way to analyze time series. In this paper, we present an approach to measure the uncertainty of non-stationary time series named higher-order multiscale fractional cumulative residual entropy. We describe how fractional cumulative residual entropy may be calculated based on second-order, third-order, fourth-order statistical moments and multiscale method. The implementation of higher-order multiscale fractional cumulative residual entropy is illustrated with simulated time series generated by uniform distribution on [0, 1]. Finally, we present the application of higher-order multiscale fractional cumulative residual entropy in logistic map time series and stock markets time series, respectively.

PROPERTIES FOR GENERALIZED CUMULATIVE PAST MEASURES OF INFORMATION

2018 ◽  
Vol 34 (1) ◽  
pp. 92-111 ◽  
Author(s):  
Camilla Calì ◽  
Maria Longobardi ◽  
Jorge Navarro
Keyword(s):  
Distribution Function ◽  
Probability Density Function ◽  
Survival Function ◽  
Residual Entropy ◽  
Coherent Systems ◽  
Underlying Distribution ◽  
Information Measures ◽  
Cumulative Residual Entropy ◽  
Past Entropy ◽  
Cumulative Residual

AbstractThe Shannon entropy based on the probability density function is a key information measure with applications in different areas. Some alternative information measures have been proposed in the literature. Two relevant ones are the cumulative residual entropy (based on the survival function) and the cumulative past entropy (based on the distribution function). Recently, some extensions of these measures have been proposed. Here, we obtain some properties for the generalized cumulative past entropy. In particular, we prove that it determines the underlying distribution. We also study this measure in coherent systems and a closely related generalized past cumulative Kerridge inaccuracy measure.

A CUMULATIVE RESIDUAL INACCURACY MEASURE FOR COHERENT SYSTEMS AT COMPONENT LEVEL AND UNDER NONHOMOGENEOUS POISSON PROCESSES

2020 ◽  
pp. 1-26
Author(s):  
Vanderlei da Costa Bueno ◽  
Narayanaswamy Balakrishnan
Keyword(s):  
Reliability Theory ◽  
Poisson Processes ◽  
Residual Entropy ◽  
Coherent Systems ◽  
Component Level ◽  
Martingale Approach ◽  
Information Measures ◽  
Cumulative Residual Entropy ◽  
Nonhomogeneous Poisson Processes ◽  
Cumulative Residual

Inaccuracy and information measures based on cumulative residual entropy are quite useful and have attracted considerable attention in many fields including reliability theory. Using a point process martingale approach and a compensator version of Kumar and Taneja's generalized inaccuracy measure of two nonnegative continuous random variables, we define here an inaccuracy measure between two coherent systems when the lifetimes of their common components are observed. We then extend the results to the situation when the components in the systems are subject to failure according to a double stochastic Poisson process.

scholarly journals Generalized Cumulative Residual Entropy for Distributions with Unrestricted Supports

2008 ◽  
Vol 2008 ◽  
pp. 1-5 ◽  
Author(s):  
Noomane Drissi ◽  
Thierry Chonavel ◽  
Jean Marc Boucher
Keyword(s):  
System Identification ◽  
Residual Entropy ◽  
Moment Problems ◽  
Differential Entropy ◽  
Power Moment ◽  
Optimization Criteria ◽  
Cumulative Residual Entropy ◽  
Cumulative Residual ◽  
Definition Of ◽  
Positive Support

We consider the cumulative residual entropy (CRE) a recently introduced measure of entropy. While in previous works distributions with positive support are considered, we generalize the definition of CRE to the case of distributions with general support. We show that several interesting properties of the earlier CRE remain valid and supply further properties and insight to problems such as maximum CRE power moment problems. In addition, we show that this generalized CRE can be used as an alternative to differential entropy to derive information-based optimization criteria for system identification purpose.

Relation Between Cumulative Residual Entropy and Excess Wealth Transform with Applications to Reliability and Risk

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
N. Unnikrishnan Nair ◽  
B. Vineshkumar
Keyword(s):  
Risk Measures ◽  
Real Life ◽  
Residual Entropy ◽  
Information Measures ◽  
Life Data ◽  
Real Life Data ◽  
Cumulative Residual Entropy ◽  
Cumulative Residual ◽  
Theoretical Results

Abstract Dynamic cumulative residual entropy is a new addition to the class of information measures. In the present paper, we study its relationship with excess wealth transform and derive some identities connecting the two using the quantile-based approach. Some theoretical results that have applications to infer ageing properties and risk measures are presented. These are used as tools to analyse real life data.

Generalized Cumulative Residual Entropy of Time Series Based on Permutation Patterns

2021 ◽  
pp. 2150055
Author(s):  
Qin Zhou ◽  
Pengjian Shang
Keyword(s):  
Time Series ◽  
Stock Markets ◽  
Multiple Scales ◽  
Permutation Entropy ◽  
Residual Entropy ◽  
Permutation Patterns ◽  
Cumulative Residual Entropy ◽  
The Us ◽  
Cumulative Residual ◽  
Different Characteristics

Cumulative residual entropy (CRE) has been suggested as a new measure to quantify uncertainty of nonlinear time series signals. Combined with permutation entropy and Rényi entropy, we introduce a generalized measure of CRE at multiple scales, namely generalized cumulative residual entropy (GCRE), and further propose a modification of GCRE procedure by the weighting scheme — weighted generalized cumulative residual entropy (WGCRE). The GCRE and WGCRE methods are performed on the synthetic series to study properties of parameters and verify the validity of measuring complexity of the series. After that, the GCRE and WGCRE methods are applied to the US, European and Chinese stock markets. Through data analysis and statistics comparison, the proposed methods can effectively distinguish stock markets with different characteristics.

scholarly journals Generalized Entropies, Variance and Applications

Entropy ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 709 ◽  
Author(s):  
Abdolsaeed Toomaj ◽  
Antonio Di Crescenzo
Keyword(s):  
Residual Entropy ◽  
Dispersion Measure ◽  
Homogeneous Poisson Process ◽  
Cumulative Residual Entropy ◽  
Excess Wealth Order ◽  
Dynamic Version ◽  
Cumulative Residual ◽  
Non Homogeneous Poisson Process ◽  
Generalized Entropies ◽  
Cumulative Entropy

The generalized cumulative residual entropy is a recently defined dispersion measure. In this paper, we obtain some further results for such a measure, in relation to the generalized cumulative residual entropy and the variance of random lifetimes. We show that it has an intimate connection with the non-homogeneous Poisson process. We also get new expressions, bounds and stochastic comparisons involving such measures. Moreover, the dynamic version of the mentioned notions is studied through the residual lifetimes and suitable aging notions. In this framework we achieve some findings of interest in reliability theory, such as a characterization for the exponential distribution, various results on k-out-of-n systems, and a connection to the excess wealth order. We also obtain similar results for the generalized cumulative entropy, which is a dual measure to the generalized cumulative residual entropy.

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