Functional Spectral Analysis

Functional Spectral Analysis is a mathematical framework within functional time series analysis that characterizes the frequency-domain structure of stochastic processes in Hilbert spaces by decomposing their autocovariance operators into spectral components.

105

Publications

6.2K

Citations

269

Authors

169

Institutions

Publications per year

2017–2026

18

Authors

269

  1. GP
    Gorka Peris

    Yale University, United States

    2 publications · 168 citations

    2

    h-index

  2. AS
    Anuj Srivastava

    Florida State University, United States

    2 publications · 189 citations

    2

    h-index

  3. JO
    J. O. Ramsay

    McGill University, Canada

    2 publications · 189 citations

    2

    h-index

  4. RC
    Robert C. Williamson

    Australian National University, Australia

    2 publications · 62 citations

    2

    h-index

  5. JS
    John Shawe‐Taylor

    University College London, United Kingdom

    2 publications · 62 citations

    2

    h-index

1–5 of 269

Venues

  1. Journal of Functional Analysis

    6 publications · 379 citations

    6

    h-index

  2. Optics Letters

    2 publications · 73 citations

    2

    h-index

  3. Mathematics of the USSR-Izvestiya

    2 publications · 511 citations

    2

    h-index

  4. arXiv (Cornell University)

    Repository · 2 publications · 28 citations

    2

    h-index

  5. Journal of Nonlinear Science

    2 publications · 28 citations

    2

    h-index

1–5