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This paper investigates the use of artificial neural networks (ANNs) to replace traditional algorithms and manual review for identifying anomalies in vehicle run data. The specific data used for this study is from undersea vehicle…

Neural and Evolutionary Computing · Computer Science 2016-03-17 Adam J. Last

One of the most popular methods for continual learning with deep neural networks is Elastic Weight Consolidation (EWC), which involves computing the Fisher Information. The exact way in which the Fisher Information is computed is however…

Machine Learning · Computer Science 2025-02-18 Gido M. van de Ven

We derive upper bounds on the quantum Fisher information in interferometry with $N$ subsystems, e.g. two-level atoms or Gaussian modes, in the presence of arbitrarily correlated Gaussian dephasing including independent and collective…

Quantum Physics · Physics 2014-03-06 Katarzyna Macieszczak

Expected Fisher information can be found a priori and as a result its inverse is the primary variance approximation used in the design of experiments. This is in contrast to the common claim that the inverse of observed Fisher information…

Methodology · Statistics 2022-08-04 Adam Lane

The dynamics of a charged two-qubit system prepared initially in a maximum entangled state is discussed, where each qubit interacts independently with a dephasing channel. The Fisher information is used to estimate the channel and the…

Quantum Physics · Physics 2016-12-13 Hamada El-Shiekh Nour Zidan , Nasser Metwally

One of the key challenges in performing muon experiments is knowing which temperatures and applied fields to measure at, and how many muon decays should be measured at each temperature/field combination to get the most useful dataset. We…

High Energy Physics - Experiment · Physics 2025-11-12 Alex Sampson , Peter J. Baker , Lucas Wilkins , John M. Wilkinson

Classically, Fisher information is the relevant object in defining optimal experimental designs. However, for models that lack certain regularity, the Fisher information does not exist and, hence, there is no notion of design optimality…

Statistics Theory · Mathematics 2019-12-04 Yi Lin , Ryan Martin , Min Yang

This paper provides a systematic approach to semiparametric identification that is based on statistical information as a measure of its "quality". Identification can be regular or irregular, depending on whether the Fisher information for…

Statistics Theory · Mathematics 2021-07-01 Juan Carlos Escanciano

Accurate channel modeling is the foundation of communication system design. However, the traditional measurement-based modeling approach has increasing challenges for the scenarios with insufficient measurement data. To obtain enough data…

Information Theory · Computer Science 2021-12-02 Zirui Wen , Ruisi He , Bo Ai , Chen Huang , Mi Yang , Zhangdui Zhong

The Fisher information matrix (FIM) is a key quantity in statistics as it is required for example for evaluating asymptotic precisions of parameter estimates, for computing test statistics or asymptotic distributions in statistical testing,…

Methodology · Statistics 2023-02-07 Maud Delattre , Estelle Kuhn

Many real-world tasks include some kind of parameter estimation, i.e., determination of a parameter encoded in a probability distribution. Often, such probability distributions arise from stochastic processes. For a stationary stochastic…

Quantum Physics · Physics 2023-06-08 Marco Radaelli , Gabriel T. Landi , Kavan Modi , Felix C. Binder

The optimal power adaptation problem is investigated for vector parameter estimation according to various Fisher information based optimality criteria. By considering an observation model that involves a linear transformation of the…

Signal Processing · Electrical Eng. & Systems 2021-10-19 Doğa Gürgünoğlu , Berkan Dulek , Sinan Gezici

The robust estimation of dynamically changing features, such as the position of prey, is one of the hallmarks of perception. On an abstract, algorithmic level, nonlinear Bayesian filtering, i.e. the estimation of temporally changing signals…

Neurons and Cognition · Quantitative Biology 2022-01-05 Anna Kutschireiter , Simone Carlo Surace , Henning Sprekeler , Jean-Pascal Pfister

Quantum Fisher information is a central quantity in quantum metrology. We discuss an alternative representation of quantum Fisher information for unitary parametrization processes. The highlight of this representation is that all…

Quantum Physics · Physics 2015-02-25 Jing Liu , Xiaoxing Jing , Xiaoguang Wang

We estimate the teleported and the gained parameters by means of Fisher information in a non-inertial frame. The sender and the receiver share an accelerated maximum or partial entangled state. The estimation degree of these parameters…

Quantum Physics · Physics 2017-03-27 N. Metwally

Collective movements are pervasive behaviours among social organisms and have led to the development of many models. However, modelling animal trajectories and social interactions in simple bounded environments remains a challenge.…

Neurons and Cognition · Quantitative Biology 2018-11-28 Leo Cazenille , Nicolas Bredeche , José Halloy

The expected decrease in system inertia and frequency stability motivates the development and maintenance of dynamic system models by Transmission System Operators. However, some dynamic model parameters can be unavailable due to market…

Signal Processing · Electrical Eng. & Systems 2025-05-27 Dawn Virginillo , Asja Derviškadić , Mario Paolone

Quantum Fisher information (QFI) plays a vital role in quantum precision measurement, quantum information, many-body physics, and other domains. Obtaining the QFI from experiment for a quantum state reveals insights such as the limits of…

Quantum Physics · Physics 2024-08-26 Qi Liu

A relationship between the Fisher information and the characteristic function is established with the help of two inequalities. A necessary and sufficient condition for equality is found. These results are used to determine the asymptotic…

Information Theory · Computer Science 2010-07-12 Cihan Tepedelenlioglu , Mahesh K. Banavar , Andreas Spanias

End-to-end trained convolutional neural networks have led to a breakthrough in optical flow estimation. The most recent advances focus on improving the optical flow estimation by improving the architecture and setting a new benchmark on the…

Computer Vision and Pattern Recognition · Computer Science 2021-06-03 D. B. de Jong , F. Paredes-Vallés , G. C. H. E. de Croon