## Abstract Dataβdriven statistical methods are useful for examining the spatial organization of human brain function. Cluster analysis is one approach that aims to identify spatial classifications of temporal brain activity profiles. Numerous clustering algorithms are available, and no one method
Methods for data analysis in classification and control
β Scribed by Rainer Palm; Rudolf Kruse
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 200 KB
- Volume
- 85
- Category
- Article
- ISSN
- 0165-0114
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
In this paper a unified description of classification methods in situations with multicollinear data is proposed. It is shown that a number of the well-established methods can be derived by substituting different modified versions of the covariance matrix into either the classical Bayes method or Fi
General steady-state data reconciliation with both measured and un-measured variables is treated through theoretical vector space methods. Instead of solving the initial equality constrained optimization problem, a parametrized regular least squares regression onto the null space of the Jacobian mat
This paper is concerned with the numerical solution of a linearly constrained quadratic programming problem by methods that use a splitting of the objective matrix. We present an acceleration step for a general splitting algorithm and we establish the convergence of the resulting accelerated scheme.