An approximation algorithm for computing the k-error linear complexity of sequences using the discrete fourier transform.
Alexandra AlecuAna SalageanPublished in: ISIT (2008)
Keyphrases
- experimental evaluation
- preprocessing
- learning algorithm
- cost function
- times faster
- k means
- dynamic programming
- objective function
- error bounds
- theoretical analysis
- worst case
- particle swarm optimization
- simulated annealing
- improved algorithm
- tree structure
- expectation maximization
- data sets
- optimal solution
- linear programming
- input data
- high accuracy
- computationally efficient
- np hard
- hidden markov models
- monte carlo
- search space
- computational complexity
- convergence rate
- approximation methods
- approximation ratio