FPGA Implementation of EVD Processor for Fast ICA Application

K. Samyuktha; Dr. K. S. Rao

A novel hardware architecture based on the extended Jacobi method is presented to solve the calculation of eigenvectors and eigen values inside a FPGA, with high accuracy, taking low execution time and using a reduced number of internal resources. Besides, the execution time is lower than an optimal algorithm to solve the eigen problem in any circuitry. Extended Jacobi method is used to calculate eigen vectors for any real time matrix with less number of operations and with less processing time. This decomposition generally goes under the name "matrix diagonalization." However, this moniker is less than optimal, since the process being described is really the decomposition of a matrix into a product of three other matrices, only one of which is diagonal, and also because all other standard types of matrix decomposition use the term "decomposition".

Select Volume / Issues:

• Volume 3 Issue 6, Nov. 2012

Year:

2012

Type of Publication:

Article

Keywords:

E V D; ICA; Eigen; Digitalization; P C A; Gaussian; Jacobi eigenvalue algorithm; ecomposition

Journal:

IJECCE

Volume:

3

Number:

6

Pages:

1432-1435

Month:

November