Results 51 to 60 of about 10,692,124 (255)
The three-parameter Logistic model (3PLM) and the four-parameter Logistic model (4PLM) have been proposed to reduce biases in cases of response disturbances, including random guessing and carelessness. However, they could also influence the examinees who
Xiaozhu Jian, Dai Buyun, Deng Yuanping
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Single shot parameter estimation via continuous quantum measurement
We present filtering equations for single shot parameter estimation using continuous quantum measurement. By embedding parameter estimation in the standard quantum filtering formalism, we derive the optimal Bayesian filter for cases when the parameter ...
A. Holevo +10 more
core +1 more source
Transformer-Based Parameter Estimation in Statistics
Parameter estimation is one of the most important tasks in statistics, and is key to helping people understand the distribution behind a sample of observations.
Xiaoxin Yin, David S. Yin
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The authors propose to implement conditional non-linear optimal perturbation related to model parameters (CNOP-P) through an ensemble-based approach. The approach was first used in our earlier study and is improved to be suitable for calculating CNOP-P ...
Xudong Yin +3 more
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Parameter Estimation of LFM Signals Based on FOTD-CFRFT under Impulsive Noise
Due to the short duration and high amplitude characteristics of impulsive noise, these parameter estimation methods based on Gaussian assumptions are ineffective in the presence of impulsive noise. To address this issue, a LFM signal parameter estimation
Houyou Wang, Yong Guo, Lidong Yang
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Parameter estimation with Sandage-Loeb test
The Sandage-Loeb (SL) test directly measures the expansion rate of the universe in the redshift range of $2\lesssim z\lesssim 5$ by detecting redshift drift in the spectra of Lyman-$\alpha$ forest of distant quasars.
Geng, Jia-Jia +2 more
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Sensitivity optimization in quantum parameter estimation [PDF]
We present a general framework for sensitivity optimization in quantum parameter estimation schemes based on continuous (indirect) observation of a dynamical system. As an illustrative example, we analyze the canonical scenario of monitoring the position
A. Barchielli +23 more
core +4 more sources
Parameter estimation in quantum sensing based on deep reinforcement learning
Parameter estimation is a pivotal task, where quantum technologies can enhance precision greatly. We investigate the time-dependent parameter estimation based on deep reinforcement learning, where the noise-free and noisy bounds of parameter estimation ...
Tailong Xiao, Jianping Fan, Guihua Zeng
doaj +1 more source
In real applications, one common issue of parameter estimation using ensemble-based data assimilation methods is the accumulation of sampling errors when a large number of observations are used to update single-value parameters.
Zheqi Shen +4 more
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Parameter Identification and State-of-Charge Estimation for Lithium-Ion Batteries Using Separated Time Scales and Extended Kalman Filter [PDF]
Kuo Yang, Yugui Tang, Zhen Zhang
openalex +1 more source

