Results 81 to 90 of about 72,703 (318)

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

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, Muhammad Zulqarnain Zeb, Muhammad Husnain Zeb, Babar Shabbir   +3 more
wiley   +1 more source

Sea Clutter Suppression Method Based on Correlation Features

Journal of Marine Science and Engineering
Radar target detection in a sea clutter environment is of significant importance in both civilian and military applications, with the detection of small maneuvering targets being particularly challenging.
Zhen Li, Huafeng He, Liyuan Wang, Tao Zhou, Yizhe Sun, Yaomin He   +5 more
doaj   +1 more source

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

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

On Grothendieck Subspaces [PDF]

Siberian Mathematical Journal, 2005
The modulus of an order bounded functional on a Riesz space is the sum of a pair of Riesz homomorphisms if and only if the kernel of this functional is a Grothendieck subspace of the ambient Riesz space. An operator version of this fact is given.
openaire   +3 more sources

Subspace-by-subspace preconditioners for structured linear systems [PDF]

Numerical Linear Algebra with Applications, 1999
Preconditioners for \(n\) by \(n\) real symmetric positive definite linear systems of equations \(Ax=b\) are constructed under the assumption \(A=\sum _{i=1}^e E_i\), each element \(E_i\) is positive semi-definite. First, element-by-element (EBE) preconditioners are reminded, see, e.g., \textit{T.~J.~R. Hughes, I.~Levit} and \textit{J.~Winget} [Comput.
Daydé, Michel, Décamps, Jérôme, P., Gould, Nicholas, I. M.   +2 more
openaire   +3 more sources

Robust neurofuzzy rule base knowledge extraction and estimation using subspace decomposition combined with regularization and D-optimality [PDF]

, 2004
A new robust neurofuzzy model construction algorithm has been introduced for the modeling of a priori unknown dynamical systems from observed finite data sets in the form of a set of fuzzy rules.
Harris, C. J., Hong, X., Harris, C.J., Chen, S.   +3 more
core   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source

Subspace Complexity Reduction in Direction-of-Arrival Estimation via the RASA Algorithm

Sensors
The complexity and scale of contemporary datasets are increasing, making the need for reliable and effective subspace processing more pressing. In array signal processing, the quality of the projection matrix and the structure of the noise subspace have ...
Belan Bapir-Bakr, Haitham Kareem-Ali, Sandra Gutiérrez-Serrano, Nerea del-Rey-Maestre, Carlos Hernández-Fernández   +4 more
doaj   +1 more source

A NEW REPRESENTATION RESULT FOR STOCHASTIC DIFFERENTIAL EQUATIONS WITH INFINITE MARKOV JUMPS AND MULTIPLICATIVE NOISE [PDF]

Fiabilitate şi Durabilitate, 2012
In this paper we give a new representation of the conditional mean square of the solutions for a classof stochastic differential linear equations with infinite Markov jumps (SDELMs) and multiplicative noise. Theobtained result is related to the solutions
Viorica Maria Ungureanu
doaj  

A rough set based subspace clustering technique for high dimensional data

Journal of King Saud University: Computer and Information Sciences, 2020
Subspace clustering aims at identifying subspaces for cluster formation so that the data is categorized in different perspectives. The conventional subspace clustering algorithms explore dense clusters in all the possible subspaces.
B. Jaya Lakshmi, M. Shashi, K.B. Madhuri
doaj   +1 more source