Adaptive filtering using fast affine projection adaptation
AssigneeNational Research Council of Canada
InventorHeping Ding
Life of this patent
Estimating the term…
Abstract
A method of adaptive filtering using fast affine projection (FAP) that allows for direct solution of the projected error vector from the autocorrelation matrix using a backward and forward recursion technique or LDLT factorization of the autocorrelation matrix followed by forward substitution, scaling and backward substitution. The method results in less computational complexity in the implementation, while still having good stability and fast convergence.
Claims20
A method of adaptive filtering using a fast affine projection adaptive filter, comprising steps of:
- (a) initializing adaptive filter coefficients of the filter;
- (b) updating the adaptive filter coefficients by:
- (i) setting a normalized step size;
- (ii) determining autocorrelation matrix coefficients of an autocorrelation matrix RN from a reference input signal;
- (iii) directly determining a projected error vector εN(n+1) by solving an N-th order positive-definite system of linear equations RNε(n+1)=eN (n+1) using a backward recursion, followed by a forward recursion, on a known projected error vector εN (n), where eN (n+1) is a prefixed, one position down shifted version of the current output signal vector eN (n) scaled in accordance with the normalized step size;
- (iv) updating the adaptive filter coefficients in accordance with coefficients of the projected error vector;
- and
- (c) repeating step (b) as required.
A method of adaptive filtering using a fast affine projection adaptive filter, comprising steps of:
- (a) initializing adaptive filter coefficients of the filter;
- (b) updating the adaptive filter coefficients by:
- (i) determining autocorrelation matrix coefficients of an autocorrelation matrix RN from a reference input signal;
- (ii) directly determining a projected error vector εN (n) by solving an N-th order positive-definite system of linear equations RNε(n)=eN (n) using an LDLT factorization of the autocorrelation matrix and solving the system of linear equations by forward substitution, scaling and back substitution;
- (iii) updating the adaptive filter coefficients in accordance with the projected error vector;
- and
- (c) repeating step (b) as required.
Dependencies are inferred from the claim text.