TSIRM: A two-stage iteration with least-squares residual minimization algorithm to solve large sparse linear and nonlinear systems.
Raphaël CouturierLilia Ziane KhodjaChristophe GuyeuxPublished in: J. Comput. Sci. (2016)
Keyphrases
- least squares
- objective function
- detection algorithm
- learning algorithm
- computational complexity
- similarity measure
- preprocessing
- dynamic programming
- levenberg marquardt
- simulated annealing
- cost function
- np hard
- search space
- k means
- significant improvement
- optimal solution
- sparse linear
- segmentation algorithm
- high dimensional
- sparse matrix
- neural network
- curve fitting
- error function
- efficient algorithms for solving
- iterative process
- optimization algorithm
- parameter estimation
- particle swarm optimization
- worst case
- probabilistic model
- artificial neural networks