Skip to main navigation
Skip to search
Skip to main content
Penn State Home
Help & FAQ
Link opens in a new tab
Search content at Penn State
Home
Researchers
Research output
Research units
Equipment
Grants & Projects
Prizes
Activities
Parsimonious model identification via atomic norm minimization
K. Bekiroglu
, B. Yilmaz
,
C. Lagoa
, M. Sznaier
Electrical Engineering
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
12
Link opens in a new tab
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Parsimonious model identification via atomic norm minimization'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Computational Complexity
100%
Nuclear Norm Minimization
100%
Parsimonious Models
100%
Model Identification
100%
Stability Constraints
100%
Nonconvex
50%
Linear Combination
50%
Moment Approach
50%
Small-sized
50%
Least Absolute Shrinkage and Selection Operator (LASSO)
50%
Sparse Representation
50%
Model Order
50%
Atomic Norm
50%
Non-uniform Sampling
50%
Time-domain Measurements
50%
LTI Systems
50%
Frequency-domain Measurement
50%
Lightly Damped Structures
50%
Unknown Initial Conditions
50%
Order Constraint
50%
Computer Science
Computational Complexity
100%
Identification Model
100%
Uniform Sampling
50%
Frequency Domain
50%
Linear Combination
50%
Research Effort
50%
Regularization
50%
Efficient Algorithm
50%
Sparse Representation
50%
Initial Condition
50%
Nuclear Norm
50%
Engineering
Computational Complexity
100%
Atomic Norm Minimization
100%
Simple Model
50%
Time Domain
50%
Frequency Domain
50%
Initial Condition
50%
Linear Combination
50%
Regularization
50%
Substantial Increase
50%
Mathematics
Experimental Data
100%
Linear Combination
50%
Initial Condition
50%
Simple Model
50%
Regularization
50%
Nonuniform
50%
Frequency Domain
50%
Time Domain
50%