Results 61 to 70 of about 21,965 (264)
Staged Diversity‐Constrained Machine Learning for High‐Dimensional Reaction Condition Optimization
Angewandte Chemie, EarlyView.Staged diversity‐constrained modeling enables efficient navigation of high‐dimensional reaction spaces, validated on cross‐coupling HTE data and applied to ruthenium‐catalyzed meta‐C─H functionalization. ABSTRACT Optimizing reaction conditions in high‐dimensional chemical spaces remains a central challenge in modern synthesis.
Shu‐Wen Li +5 more
wiley +2 more sources
Adaptive Predictive Control: A Data-Driven Closed-Loop Subspace Identification Approach
Abstract and Applied Analysis, 2014 This paper presents a data-driven adaptive predictive control method using closed-loop subspace identification. As the predictor is the key element of the predictive controller, we propose to derive such predictor based on the subspace matrices which are
Xiaosuo Luo, Yongduan Song
doaj +1 more source
Sparse signal subspace decomposition based on adaptive over-complete dictionary
EURASIP Journal on Image and Video Processing, 2017 This paper proposes a subspace decomposition method based on an over-complete dictionary in sparse representation, called “sparse signal subspace decomposition” (or 3SD) method. This method makes use of a novel criterion based on the occurrence frequency
Hong Sun +2 more
doaj +1 more source
Subspace methods for three‐parameter eigenvalue problems [PDF]
Numerical Linear Algebra with Applications, 2019 SummaryWe propose subspace methods for three‐parameter eigenvalue problems. Such problems arise when separation of variables is applied to separable boundary value problems; a particular example is the Helmholtz equation in ellipsoidal and paraboloidal coordinates.
Hochstenbach, Michiel E. +3 more
openaire +5 more sources
Advanced Intelligent Discovery, EarlyView.This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah +3 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley +1 more source
Signal Subspace Speech Enhancement with Oblique Projection and Normalization [PDF]
Radioengineering, 2017 In this paper, a subspace speech enhancement method handling colored noise using oblique projection is proposed. Perceptual features and variance normalization are used to reduce residual noise and improve speech intelligibility of the output. Initially,
S. Surendran, T. K. Kumar
doaj
Millimeter Wave Channel Estimation Based on Subspace Fitting
IEEE Access, 2018 We consider the channel estimation of millimeter wave (mmWave) multiple-input multiple-output systems, where both the transmitter and receiver adopt hybrid beamforming structure.
Didi Zhang +3 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source