Results 51 to 60 of about 3,141,344 (325)
Open-Ended Evolutionary Robotics: an Information Theoretic Approach [PDF]
, 2010 This paper is concerned with designing self-driven fitness functions for Embedded Evolutionary Robotics. The proposed approach considers the entropy of the sensori-motor stream generated by the robot controller.
A. Baranes +16 more
core +4 more sources
Entropy, 2019 This study presents a comprehensive fault diagnosis method for rolling bearings. The method includes two parts: the fault detection and the fault classification.
Weibo Zhang, Jianzhong Zhou
semanticscholar +1 more source
Universally Typical Sets for Ergodic Sources of Multidimensional Data [PDF]
, 2013 We lift important results about universally typical sets, typically sampled sets, and empirical entropy estimation in the theory of samplings of discrete ergodic information sources from the usual one-dimensional discrete-time setting to a ...
Krueger, Tyll +3 more
core +2 more sources
Molecular Oncology, EarlyView.Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova +14 more
wiley +1 more source
Understanding the Fractal Dimensions of Urban Forms through Spatial Entropy
Entropy, 2017 The spatial patterns and processes of cities can be described with various entropy functions. However, spatial entropy always depends on the scale of measurement, and it is difficult to find a characteristic value for it.
Yanguang Chen, Jiejing Wang, Jian Feng
doaj +1 more source
A Review of Shannon and Differential Entropy Rate Estimation
Entropy, 2021 In this paper, we present a review of Shannon and differential entropy rate estimation techniques. Entropy rate, which measures the average information gain from a stochastic process, is a measure of uncertainty and complexity of a stochastic process. We
Andrew Feutrill, Matthew Roughan
doaj +1 more source
Variable Selection Bias in Classification Trees Based on Imprecise Probabilities [PDF]
, 2005 Classification trees based on imprecise probabilities provide an advancement of classical classification trees. The Gini Index is the default splitting criterion in classical classification trees, while in classification trees based on imprecise ...
Strobl, Carolin
core +3 more sources
Empirical Risk Minimization With Relative Entropy Regularization
IEEE Transactions on Information TheoryThe empirical risk minimization (ERM) problem with relative entropy regularization (ERM-RER) is investigated under the assumption that the reference measure is a $σ$-finite measure, and not necessarily a probability measure. Under this assumption, which leads to a generalization of the ERM-RER problem allowing a larger degree of flexibility for ...
Samir M. Perlaza +4 more
openaire +3 more sources
FEBS Open Bio, EarlyView.Amino acids sequence of two different proteins with the same sequence (chameleon sequence—black boxes) represent in 3D structure of the proteins different secondary structures: HHHH—helical and BBB—Beta‐structural. The chains folded in water environment adopt different III‐order structures in which the chameleon fragments appear to adopt similar status
Irena Roterman +4 more
wiley +1 more source
Entropy Estimation From Ranked Set Samples With Application to Test of Fit
Revista Colombiana de Estadística, 2017 This article deals with entropy estimation using ranked set sampling (RSS). Some estimators are developed based on the empirical distribution function and its nonparametric maximum likelihood competitor. The suggested entropy estimators have smaller root
Ehsan Zamanzade , Mahdi Mahdizadeh
doaj +1 more source