Tomographic reconstruction using a minimum variance estimator
โ Scribed by Gary Beihl
- Publisher
- Springer US
- Year
- 1984
- Tongue
- English
- Weight
- 68 KB
- Volume
- 8
- Category
- Article
- ISSN
- 0148-5598
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
A stationary estimator is presented that provides estimates for both the outputs and the inputs of linear timeinvariant systems. The estimates satisfy the input-output equations and are optimal in a weighted minimum variance sense. It is shown that the true optimum problem is too complicated to allo
The classical way to solve the problem of predicting future values of a stationary non-zero mean stochastic process having known model is (i) to remove the mean of the process from the past data, (ii) to apply an optimal predictor (Wiener, Levinson. Kalman,. . ) to the zero-mean purely stochastic r