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Contributions and structure of the thesis

This thesis consists of eight publications and an introductory part with literature survey. The aim of the thesis is to develop a computationally efficient algorithm for a nonlinear extension of the linear factor analysis model.

Section 2 of the introductory part summarises the publications of the thesis, with the contributions of the author explained. Section 3 outlines the theoretical framework of Bayesian probability theory and decision theory. Practical methods and approximations together with their connection to information theory are discussed in section 4. Section 5 introduces the basic static Gaussian linear factor analysis model and its non-Gaussian, nonlinear and dynamic extensions. Publication V serves as a detailed account on the nonlinear factor analysis method developed in this thesis but section 6 gives a brief summary. Biological relevance and further lines of research are discussed in section 7.


next up previous contents
Next: PUBLICATIONS OF THE THESIS Up: INTRODUCTION Previous: INTRODUCTION
Harri Valpola
2000-10-31