ICA 2007

ICA 2007
7th International Conference on
Independent Component Analysis
and Signal Separation

London, UK        9 - 12 September 2007

Banner showing images of London
- Home
- Committee
- Call for Papers
- Submission
- Info for Presenters
- Dates
- Programme
- Tutorials
- Keynotes
- Papers
- Registration
- Accommodation
- Venue
- Maps
- Arrival
- Travel Tips
- Links
- Contact

Paper No: 64

Estimating the mixing matrix in Sparse Component Analysis based on converting a multiple dominant to a single dominant problem

Author(s): Nima Noorshams, Babaie-Zadeh Massoud, Christian Jutten


We propose a new method for estimating the mixing matrix, A, in the linear model x(t)=A s(t), t=1,...,T$, for the problem of underdetermined Sparse Component Analysis (SCA). Contrary to most previous algorithms, there can be more than one dominant source at each instant (we call it a ``multiple dominant'' problem). The main idea is to convert the multiple dominant problem to a series of single dominant problems, which may be solved by well-known methods. Each of these single dominant problems results in the determination of some columns of A. This results in a huge decrease in computations, which lets us to solve higher dimension problems that were not possible before.

Last Updated: 14-Aug-2007   Please read our disclaimer