Robustness of the Filtered-X LMS Algorithm - Part I: Necessary Conditions for Convergence and the Asymptotic Pseudospectrum of Toeplitz Matrices.
Rufus FraanjeMichel VerhaegenStephen J. ElliottPublished in: IEEE Trans. Signal Process. (2007)
Keyphrases
- learning algorithm
- detection algorithm
- optimization algorithm
- np hard
- optimal solution
- computational complexity
- preprocessing
- k means
- significant improvement
- computational cost
- convergence property
- convergence rate
- matching algorithm
- worst case
- high accuracy
- iterative algorithms
- clustering method
- rapid convergence
- probabilistic model
- dynamic programming
- cost function
- similarity measure
- sufficient conditions
- linear programming
- computational efficiency
- convex optimization
- objective function
- sparse matrix
- decision trees