This paper presents D-optimal experimental designs for a variety of non-linear models which depend on an arbitrary number of covariates but assume a positive prior mean and a Fisher information matrix satisfying particular properties. It is argued that these optimal designs can be regarded as a ÿrst
Optimal Non-Linear Models for Sparsity and Sampling
✍ Scribed by Akram Aldroubi; Carlos Cabrelli; Ursula Molter
- Publisher
- SP Birkhäuser Verlag Boston
- Year
- 2008
- Tongue
- English
- Weight
- 465 KB
- Volume
- 14
- Category
- Article
- ISSN
- 1069-5869
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