Results 91 to 100 of about 255,284 (162)

Measuring Synchronization between Spikes and Local Field Potential Based on the Kullback-Leibler Divergence. [PDF]

Comput Intell Neurosci, 2021
Yin L, Zhang G, Yin F.
europepmc   +1 more source

Fault-Tolerant indoor localization based on speed conscious recurrent neural network using Kullback-Leibler divergence. [PDF]

Peer Peer Netw Appl, 2022
Varma PS, Anand V.
europepmc   +1 more source

A Deep-Learning-Based Health Indicator Constructor Using Kullback-Leibler Divergence for Predicting the Remaining Useful Life of Concrete Structures. [PDF]

Sensors (Basel), 2022
Nguyen TK, Ahmad Z, Kim JM.
europepmc   +1 more source

Interpreting Kullback-Leibler divergence with the Neyman-Pearson lemma

Kullback-Leibler divergence and the Neyman-Pearson lemma are two fundamental concepts in statistics. Both are about likelihood ratios: Kullback-Leibler divergence is the expected log-likelihood ratio, and the Neyman-Pearson lemma is about error rates of ...
Copas, John, Eguchi, Shinto
core  

Construction of an individualized brain metabolic network in patients with advanced non-small cell lung cancer by the Kullback-Leibler divergence-based similarity method: A study based on 18F-fluorodeoxyglucose positron emission tomography. [PDF]

Front Oncol, 2023
Yu J, Hua L, Cao X, Chen Q, Zeng X, Yuan Z, Wang Y.   +6 more
europepmc   +1 more source

Orthogonal nonnegative matrix factorization with the Kullback–Leibler divergence

Pattern Recognition Letters
10 pages, corrected some ...
Nkurunziza, Jean Pacifique, Nahayo, Fulgence, Gillis, Nicolas   +2 more
openaire   +4 more sources

A closed-form formula for the Kullback-Leibler divergence between Cauchy distributions

, 2019
8 pagesWe report a closed-form expression for the Kullback-Leibler divergence between Cauchy distributions which involves the calculation of a novel definite integral.
Chyzak, Frédéric, Nielsen, Frank
core   +1 more source

A Maximum Value for the Kullback–Leibler Divergence between Quantized Distributions

Information
The Kullback–Leibler (KL) divergence is a widely used measure for comparing probability distributions, but it faces limitations such as its unbounded nature and the lack of comparability between distributions with different quantum values (the discrete ...
Vincenzo Bonnici
doaj   +1 more source

Identifying critical state of complex diseases by single-sample Kullback-Leibler divergence. [PDF]

BMC Genomics, 2020
Zhong J, Liu R, Chen P.
europepmc   +1 more source

Erratum: Estimating the spectrum in computed tomography via Kullback-Leibler divergence constrained optimization. [Med. Phys. 46(1), p. 81-92 (2019)]. [PDF]

Med Phys, 2020
Ha W, Sidky EY, Foygel Barber R, Gilat Schmidt T, Pan X.   +4 more
europepmc   +1 more source