Input-output Identifiability
Input-Output Identifiability is a type of model identifiability that characterizes the extent to which the internal parameters of a system can be uniquely determined from its observed input-output behavior, distinguishing it from structural or practical identifiability by focusing exclusively on the relationship between external stimuli and responses.
10
Publications
244
Citations
24
Authors
21
Institutions
Publications per year
2017–2026
1
Parents
10
1–5 of 10
24
Massachusetts Institute of Technology, United States
1 publications · 33 citations
1
h-index
1
h-index
1
h-index
University of California, Los Angeles, United States
1 publications · 29 citations
1
h-index
1
h-index
1–5 of 24
21

Hohai University
Nanjing, China
1 h-index
2 publications
58 citations

Universidade Federal do Rio de Janeiro
Rio de Janeiro, Brazil
1 h-index
1 publications
18 citations
Marshall Space Flight Center
Redstone Arsenal, United States
1 h-index
2 publications
36 citations

National Research University Higher School of Economics
Moscow, Russia
1 h-index
1 publications
22 citations

Queens College, CUNY
New York, United States
1 h-index
1 publications
22 citations
Courant Institute of Mathematical Sciences
New York, United States
1 h-index
1 publications
22 citations
Queen's University
Kingston, Canada
1 h-index
3 publications
33 citations
New York University
New York, United States
1 h-index
1 publications
22 citations
1–8 of 21
4 publications · 99 citations
4
h-index
2 publications · 82 citations
2
h-index
1 publications · 29 citations
1
h-index
1 publications · 12 citations
1
h-index
1 publications · 11 citations
1
h-index
1–5