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Қарағанды университетінің хабаршысы. Математика сериясы, 2019 In this work, first of all, Lpw),Ө (T) weighted grand Lebesgue spaces and Muckenhoupt weights is defined. The information about properties of these spaces is given. Let Tn be the trigonometric polynomial of best approximation.
Sadulla Z. Jafarov
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Convolution Algebraic Structures Defined by Hardy-Type Operators
Journal of Function Spaces and Applications, 2013 The main aim of this paper is to show that certain Banach spaces, defined via integral kernel operators, are Banach modules (with respect to some known Banach algebras and convolution products on ℝ+).
Pedro J. Miana +2 more
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Journal of Inequalities and Applications, 2017 In this paper, the authors establish the sharp maximal estimates for the multilinear iterated commutators generated by B M O $BMO$ functions and multilinear singular integral operators with generalized kernels.
Yan Lin, Nan Zhang
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Feedback Linearisation with State Constraints
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT Feedback Linearisation (FBL) is a widely used technique that applies feedback laws to transform input‐affine nonlinear control systems into linear control systems, allowing for the use of linear controller design methods such as pole placement.
Songlin Jin, Yuanbo Nie, Morgan Jones
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Journal of Mathematical SciencesTraditional Lp spaces are fundamental in functional analysis, demarcated by the relationship $1/p + 1/q = 1$. This research pioneers the concept of $\theta$-Lebesgue space, stemming from a simultaneous weakening of both the classical $L_p$ relation and its $\theta$-variant, $1/(\theta(p)) + 1/(\theta(q)) = 1$.
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The Span of the Translations of a Function in a Lebesgue Space [PDF]
Proceedings of the National Academy of Sciences, 1944 Not ...
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AGT: Efficient Offline Reinforcement Learning With Advantage‐Guided Transformer
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Offline reinforcement learning (RL) is a paradigm that seeks to train policies directly based on fixed datasets derived from previous interactions with the environment. However, offline RL faces critical challenges in environments characterised by sparse rewards and datasets dominated by suboptimal trajectories.
Jiaye Wei +4 more
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Identifiability conditions in cognitive diagnosis: Implications for Q‐matrix estimation algorithms
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract The Q‐matrix of a cognitively diagnostic assessment (CDA), documenting the item‐attribute associations, is a key component of any CDA. However, the true Q‐matrix underlying a CDA is never known and must be estimated—typically by content experts.
Hyunjoo Kim +2 more
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Calibrating Bayesian inference
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information‐updating rules. In many applications, however, prior distributions are introduced merely as instruments to facilitate computation, rather than as representations of genuine subjective belief ...
Yang Liu +2 more
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Boundedness of Multilinear Calderón-Zygmund Operators on Grand Variable Herz Spaces
Journal of Function Spaces, 2022 In this paper, we prove the boundedness of multilinear Calderón-Zygmund operators on product of grand variable Herz spaces. These results generalize the boundedness of multilinear Calderón-Zygmund operators on product of variable exponent Lebesgue spaces
Hammad Nafis +2 more
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