Tracking Error Minimization

Tracking Error Minimization is a methodological framework within the domain of benchmark selection that aims to reduce the divergence between the performance of a target model and a predefined benchmark by systematically optimizing alignment metrics.

264

Publications

13.7K

Citations

766

Authors

344

Institutions

Publications per year

2017–2026

89

Authors

766

  1. NT
    Nhan T. Nguyen

    Ames Research Center, United States

    4 publications · 54 citations

    4

    h-index

  2. AS
    Ahmed Sabah Al-Araji

    University of Technology - Iraq, Iraq

    4 publications · 59 citations

    4

    h-index

  3. JA
    Jay A. Farrell

    University of California, Riverside, United States

    4 publications · 1.3K citations

    4

    h-index

  4. JC
    Jie Chen

    University of California, Riverside, United States

    3 publications · 257 citations

    3

    h-index

  5. GT
    Gang Tao

    University of Virginia, United States

    3 publications · 543 citations

    3

    h-index

1–5 of 766

Venues

  1. IEEE Transactions on Automatic Control

    12 publications · 3.1K citations

    12

    h-index

  2. IEEE Transactions on Industrial Electronics

    6 publications · 421 citations

    6

    h-index

  3. IET Control Theory and Applications

    6 publications · 228 citations

    6

    h-index

  4. 5

    h-index

  5. IEEE/ASME Transactions on Mechatronics

    4 publications · 122 citations

    4

    h-index

1–5