A novel gain distribution policy based on individual-coefficient convergence for PNLMS-type algorithms.
Fábio Luis PerezEduardo Vinicius KuhnFrancisco das Chagas de SouzaRui SearaPublished in: Signal Process. (2017)
Keyphrases
- learning algorithm
- convergence rate
- data structure
- orders of magnitude
- optimization problems
- computational complexity
- computational cost
- probability distribution
- combinatorial optimization
- computationally efficient
- benchmark datasets
- stochastic approximation
- iterative algorithms
- decision trees
- computational efficiency
- data distribution
- data mining algorithms
- search algorithm
- theoretical analysis
- machine learning
- worst case
- supply chain
- lower bound