A Spatially-Controlled Principal Components Analysis
β Scribed by Mark S. Monmonier
- Book ID
- 109147279
- Publisher
- John Wiley and Sons
- Year
- 2010
- Tongue
- English
- Weight
- 177 KB
- Volume
- 2
- Category
- Article
- ISSN
- 0016-7363
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
## Abstract Principal component analysis (PCA) is a multivariate technique that analyzes a data table in which observations are described by several interβcorrelated quantitative dependent variables. Its goal is to extract the important information from the table, to represent it as a set of new or
A recurrent linear network can be trained with Oja's constrained Hebbian learning rule. As a result, the network learns to represent the temporal context associated to its input sequence. The operation performed by the network is a generalization of Principal Components Analysis (PCA) to time-series