Login / Signup

Identification of Sparse Volterra Systems: An Almost Orthogonal Matching Pursuit Approach.

Changming ChengEr-Wei BaiZhike Peng
Published in: IEEE transactions on automatic control (2021)
This paper considers identification of sparse Volterra systems. A method based on the almost orthogonal matching pursuit (AOMP) is proposed. The AOMP algorithm allows one to estimate one non-zero coefficient at a time until all non-zero coefficients are found without losing the optimality and the sparsity, thus avoiding the curse of dimensionality often encountered in Volterra system identification.
Keyphrases
  • bioinformatics analysis
  • neural network
  • computed tomography
  • contrast enhanced