Abstract: Disclosed are an adaptive RLS decision feedback equalizing system, characterized by comprising: an error code cross-correlation module, an equalization module, a decision feedback unit, a coefficient updating unit and an autocorrelation estimation module. Also disclosed are an implementation method of the adaptive RLS decision feedback equalizing system, comprising the following steps: 1) setting an initial value of c0 for a filtering coefficient; 2) generating a filtering output signal yk; 3) computing an error code cross-correlation result Ik; 4) updating the filtering coefficient ck?1 to ck; 5) updating an autocorrelation inverse matrix estimation result Pk?1 to Pk according to a forget constant factor w and an equalizer input signal sequence rk; 6) repeating step 2) to step 5), until the equalizer coefficient converges.

Abstract: Disclosed are an adaptive RLS decision feedback equalizing system, characterized by comprising: an error code cross-correlation module, an equalization module, a decision feedback unit, a coefficient updating unit and an autocorrelation estimation module. Also disclosed are an implementation method of the adaptive RLS decision feedback equalizing system, comprising the following steps: 1) setting an initial value of c0 for a filtering coefficient; 2) generating a filtering output signal yk; 3) computing an error code cross-correlation result Ik; 4) updating the filtering coefficient ck?1 to ck; 5) updating an autocorrelation inverse matrix estimation result Pk?1 to Pk according to a forget constant factor w and an equalizer input signal sequence rk; 6) repeating step 2) to step 5), until the equalizer coefficient converges.