Numerical Linear Algebra with Applications (NLAA)

Numerical Linear Algebra with Applications is an esteemed peer‑reviewed journal published by John Wiley & Sons Ltd. that serves as a primary international forum for high‑quality research in applied and computational mathematics, specifically numerical linear algebra and related computational methods. Since its launch in 1994, the journal has showcased cutting‑edge theoretical developments, algorithmic innovations and real‑world applications of numerical linear algebra techniques. Its scope spans both methodological advances in computing solutions to linear systems, eigenproblems, singular value decompositions and matrix factorizations, and practical implementations relevant to scientific computing, engineering, data science and large‑scale modelling. Articles frequently address topics such as iterative solvers, preconditioning strategies, multigrid and Krylov subspace methods, parallel algorithms, tensor computations, and the use of linear algebra algorithms in fields from computational fluid dynamics to machine learning. The journal bridges rigorous mathematical foundations with computational practice, attracting contributions from mathematicians, computer scientists and researchers across disciplines that depend on efficient linear algebra solutions. With a bimonthly schedule and rigorous peer review, Numerical Linear Algebra with Applications maintains high standards for both originality and significance, making it a respected outlet for researchers seeking to advance both theory and application in numerical computation.

Numerical Linear Algebra with Applications (NLAA) is :-

• International, Peer-Reviewed, Open Access, Refereed, Algebra and Number Theory, Applied Mathematics, analysis and implementation of linear algebra algorithms for large‑scale problems, including iterative and direct methods, eigenvalue and singular value problems, preconditioning, Krylov subspace methods, multigrid techniques, parallel algorithms and applications in areas such as computational physics, engineering, machine learning and network modeling , Online or Print , Bi-Monthly Journal

• UGC Approved, ISSN Approved: P-ISSN P-ISSN: 1070-5325, E-ISSN: 1099-1506, Established: 1994, Impact Factor: 2.1
• Does Not Provide Crossref DOI

• Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE