Pages that link to "Item:Q3139973"
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The following pages link to ASMO—Dan algorithm for adaptive spline modelling of observation data (Q3139973):
Displaying 18 items.
- ASMOD (Q14666) (← links)
- A fast learning algorithm for parsimonious fuzzy neural systems (Q1602920) (← links)
- Identification of nonlinear system structure and parameters using regime decomposition (Q1891001) (← links)
- Constructing accurate and parsimonious fuzzy models with distinguishable fuzzy sets based on an entropy measure (Q2492355) (← links)
- A model-based PID controller for Hammerstein systems using B-spline neural networks (Q2795803) (← links)
- System identification of Wiener systems with B-spline functions using De Boor recursion (Q2872640) (← links)
- Modelling and control of Hammerstein system using B-spline approximation and the inverse of De Boor algorithm (Q2935100) (← links)
- Model selection approaches for non-linear system identification: a review (Q3006178) (← links)
- Non-linear system identification using wavelet multiresolution models (Q3151500) (← links)
- An adaptive multiscale basis method for modelling discrete-time non-linear dynamical systems (Q3151616) (← links)
- Automatic steering of ships using neural networks (Q4262402) (← links)
- Theoretical properties of the ASMOD algorithm for empirical modelling (Q4353768) (← links)
- DISCRETE WAVELET MODELS FOR IDENTIFICATION AND QUALITATIVE ANALYSIS OF CHAOTIC SYSTEMS (Q4522226) (← links)
- The wavelet-NARMAX representation: A hybrid model structure combining polynomial models with multiresolution wavelet decompositions (Q4672743) (← links)
- Supervised training algorithms for B-Spline neural networks and neuro-fuzzy systems (Q4787947) (← links)
- Comparison of two construction algorithms for local model networks (Q4808248) (← links)
- A unified wavelet-based modelling framework for non-linear system identification: the WANARX model structure (Q4828434) (← links)
- Regularized orthogonal least squares algorithm for constructing radial basis function networks (Q4894037) (← links)
