Abstract This paper investigates the state consistence of parametric data-driven reduced order models (ROMs) in a state-space form obtained by various system identification methods, including autoregressive exogenous (ARX) and subspace (N4SID), for aeroelastic analysis varying flight conditions. The target envelop is first partitioned into discrete grid points, on each which an aerodynamic ROM ...

The data processing under a multi-scale framework can satisfy the problem analysis from different perspectives, and rough set model promoted development of analysis. optimal cut in decision systems enable objects to take scales same attribute, thus realize knowledge acquisition across granularity levels information systems. However, practical applications network environment, system often chang...

In recent years, deep convolutional neural networks (CNNs) have demonstrated impressive ability to represent hyperspectral images (HSIs) and achieved encouraging results in HSI classification. However, the existing CNN-based models operate at patch level, which a pixel is separately classified into classes using of around it. This patch-level classification will lead large number repeated calcu...

Grapheme-to-phoneme conversion is an important step in speech segmentation and synthesis. Many approaches are proposed in the literature to perform appropriate transcriptions: CART, FST, HMM, etc. In this paper we propose the use of an automatic algorithm that uses the transformation-based errordriven learning to match the phonetic transcription with the speaker’s dialect and style. Different t...

Finitely Supported Mathematics represents a part of mathematics for experimental sciences which has a continuous evolution in the last century. It is developed according to the Fraenkel-Mostowski axioms of set theory. The axiom of choice is inconsistent in the Finitely Supported Mathematics. We prove that several weaker forms of the axiom of choice are also inconsistent in the Finitely Supporte...

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