Uncertainty Characterization of Engineering Failure Data

2014 ◽  
Author(s):  
Zhigang Wei ◽  
Kamran Nikbin
Keyword(s):  
Information Theory ◽  
Computational Complexity ◽  
Survival Function ◽  
Distribution Functions ◽  
Uncertainty Measure ◽  
Classical Statistical Mechanics ◽  
Failure Data ◽  
Uncertainty Measurements ◽  
Uncertainty Parameter

How to quantitatively measure the uncertainty of engineering failure data is an important but still unsolved task in probabilistic risk analysis. This paper aims to fill the gap first by specifying the requirements for a robust uncertainty measure to meet the criteria. Complexity and uncertainty measurements in computational complexity, classical statistical mechanics and information theory are also reviewed for possible inspiration. In this paper, a new groundbreaking parameter, which is related to reliability or survival function, is selected to characterize the uncertainty of engineering failure data with given probabilistic distributions. The uncertainty formulae based on the Shannon entropy and the new uncertainty parameter for various distribution functions are also provided. Finally, several examples are given to demonstrate the applicability of the new uncertainty measure in durability and reliability analyses.

Nanoprobing Application on Characterization of 6T-SRAM Single Bit Failures with Different Gox Breakdown Defect

2006 ◽  
Author(s):  
Cheng-Piao Lin ◽  
Chin-Hsin Tang ◽  
Cheng-Hsu Wu ◽  
Cheng-Chun Ting
Keyword(s):  
Copper Metallization ◽  
Physical Analysis ◽  
Electrical Characteristics ◽  
Gate Leakage Current ◽  
Data Retention ◽  
Simulation Data ◽  
Failure Data ◽  
Dual Gate ◽  
Soft Breakdown

Abstract This paper analyzes several SRAM failures using nano-probing technique. Three SRAM single bit failures with different kinds of Gox breakdown defects analyzed are gross function single bit failure, data retention single bit failure, and special data retention single bit failure. The electrical characteristics of discrete 6T-SRAM cells with soft breakdown are discussed and correlated to evidences obtained from physical analysis. The paper also verifies many previously published simulation data. It utilizes a 6T-SRAM vehicle consisting of a large number of SRAM cells fabricated by deep sub-micron, dual gate, and copper metallization processes. The data obtained from this paper indicates that Gox breakdown location within NMOS pull-down device has larger a impact on SRAM stability than magnitude of gate leakage current, which agrees with previously published simulation data.

scholarly journals A Class of Shannon-McMillan theorems for mth-order Markov information source on generalized random selection system

2013 ◽  
Vol 44 (2) ◽  
pp. 131-140
Author(s):  
Wang Kang Kang ◽  
Zong De Cai
Keyword(s):  
Information Theory ◽  
Information Source ◽  
Distribution Functions ◽  
Random Selection ◽  
New Technique ◽  
Selection System ◽  
A New Technique

In this paper, our aim is to establish a class of Shannon-McMillan theorems for $m$th-order nonhomogeneous Markov information source on the generalized random selection system by constructing the consistent distribution functions. As corollaries, we obtain some Shannon-McMillan theorems for $m$th-order nonhomogeneous Markov information source and the general nonhomogeneous Markov information source. Some results which have been obtained are extended. In the proof, a new technique for studying Shannon-McMillan theorems in information theory is applied.

A logic of knowledge based on abstract arguments

2021 ◽  
Author(s):  
Yì N Wáng ◽  
Xu Li
Keyword(s):  
Computational Complexity ◽  
Model Checking ◽  
True Belief ◽  
Logical Omniscience ◽  
Knowledge Based ◽  
Logic Of Knowledge ◽  
Multi Agent ◽  
Soundness And Completeness ◽  
Base Logic

Abstract We introduce a logic of knowledge in a framework in which knowledge is treated as a kind of belief. The framework is based on a standard KD45 characterization of belief, and the characterization of knowledge undergoes the classical tripartite analysis that knowledge is justified true belief, which has a natural link to the studies of logics of evidence and justification. The interpretation of knowledge avoids the unwanted properties of logical omniscience, independent of the choice of the base logic of belief. We axiomatize the logic, prove its soundness and completeness and study the computational complexity results of the model checking and satisfiability problems. We extend the logic to a multi-agent setting and introduce a variant in which belief is characterized in a weaker system to avoid the problem of logical omniscience.

scholarly journals Characterization of Visuomotor/Imaginary Movements in EEG: An Information Theory and Complex Network Approach

2019 ◽  
Vol 7 ◽  
Author(s):  
Roman Baravalle ◽  
Natalí Guisande ◽  
Mauro Granado ◽  
Osvaldo A. Rosso ◽  
Fernando Montani
Keyword(s):  
Information Theory ◽  
Complex Network ◽  
Network Approach

scholarly journals Computing the Interleaving Distance is NP-Hard

2019 ◽  
Vol 20 (5) ◽  
pp. 1237-1271 ◽  
Author(s):  
Håvard Bakke Bjerkevik ◽  
Magnus Bakke Botnan ◽  
Michael Kerber
Keyword(s):  
Computational Complexity ◽  
Complete Characterization ◽  
Np Hard ◽  
Slight Improvement ◽  
Approximation Factor ◽  
Distance Computation ◽  
Persistence Modules ◽  
Np Complete ◽  
Interleaving Distance

Abstract We show that computing the interleaving distance between two multi-graded persistence modules is NP-hard. More precisely, we show that deciding whether two modules are 1-interleaved is NP-complete, already for bigraded, interval decomposable modules. Our proof is based on previous work showing that a constrained matrix invertibility problem can be reduced to the interleaving distance computation of a special type of persistence modules. We show that this matrix invertibility problem is NP-complete. We also give a slight improvement in the above reduction, showing that also the approximation of the interleaving distance is NP-hard for any approximation factor smaller than 3. Additionally, we obtain corresponding hardness results for the case that the modules are indecomposable, and in the setting of one-sided stability. Furthermore, we show that checking for injections (resp. surjections) between persistence modules is NP-hard. In conjunction with earlier results from computational algebra this gives a complete characterization of the computational complexity of one-sided stability. Lastly, we show that it is in general NP-hard to approximate distances induced by noise systems within a factor of 2.

scholarly journals Opacity distribution functions for stellar spectra synthesis

2019 ◽  
Vol 627 ◽  
pp. A157
Author(s):  
M. Cernetic ◽  
A. I. Shapiro ◽  
V. Witzke ◽  
N. A. Krivova ◽  
S. K. Solanki ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Spectral Synthesis ◽  
Distribution Functions ◽  
Transmission Curve ◽  
Spectral Interval ◽  
Space Telescopes ◽  
Radiative Fluxes ◽  
Stellar Spectra ◽  
Speed Up

Context. Stellar spectra synthesis is essential for the characterization of potential planetary hosts. In addition, comprehensive stellar variability calculations with fast radiative transfer are needed to disentangle planetary transits from stellar magnetically driven variability. The planet-hunting space telescopes, such as CoRoT, Kepler, and TESS, bring vast quantities of data, rekindling the interest in fast calculations of the radiative transfer. Aims. We revisit the opacity distribution functions (ODF) approach routinely applied to speed up stellar spectral synthesis. To achieve a considerable speedup relative to the state of the art, we further optimize the approach and search for the best ODF configuration. Furthermore, we generalize the ODF approach for fast calculations of flux in various filters often used in stellar observations. Methods. In a parameter-sweep fashion, we generated ODF in the spectral range from UV to IR with different setups. The most accurate ODF configuration for each spectral interval was determined. We adapted the wavelength grid based on the transmission curve for calculations of the radiative fluxes through filters before performing the normal ODF procedure. Results. Our optimum ODF configuration allows for a three-fold speedup, compared to the previously used ODF configurations. The ODF generalization to calculate fluxes through filters results in a speedup of more than two orders of magnitude.

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