摘要
Order-recursive least-squares(ORLS)algorithms are applied to the prob-lems of estimation and identification of FIR or ARMA system parameters where a fixedset of input signal samples is available and the desired order of the underlying model isunknown.On the basis of several universal formulae for updating nonsymmetric projec-tion operators,this paper presents three kinds of LS algorithms,called nonsymmetric,symmetric and square root normalized fast ORLS algorithms,respectively.As to the au-thors’ knowledge,the first and the third have not been so far provided,and the second isone of those which have the lowest computational requirement.Several simplified versionsof the algorithms are also considered.
Order-recursive least-squares(ORLS)algorithms are applied to the prob- lems of estimation and identification of FIR or ARMA system parameters where a fixed set of input signal samples is available and the desired order of the underlying model is unknown.On the basis of several universal formulae for updating nonsymmetric projec- tion operators,this paper presents three kinds of LS algorithms,called nonsymmetric, symmetric and square root normalized fast ORLS algorithms,respectively.As to the au- thors' knowledge,the first and the third have not been so far provided,and the second is one of those which have the lowest computational requirement.Several simplified versions of the algorithms are also considered.
