A Generic Clustering-Based Algorithm for Approximating IOHMM Topology and Parameters.
Gérald RocherJean-Yves TigliStéphane LavirottePublished in: IEEE Access (2021)
Keyphrases
- dynamic programming
- expectation maximization
- computational complexity
- detection algorithm
- input data
- k means
- experimental evaluation
- parameter estimation
- objective function
- parameter tuning
- optimization algorithm
- high accuracy
- times faster
- cost function
- computational cost
- improved algorithm
- preprocessing
- learning algorithm
- neural network
- simulated annealing
- recognition algorithm
- maximum likelihood estimation
- theoretical analysis
- computationally efficient
- data sets
- probabilistic model
- particle swarm optimization
- matching algorithm
- parameter space
- significant improvement
- search space
- search algorithm
- optimal solution
- optimal parameters
- levenberg marquardt