1The paper discusses computationally efficient NLMS and RLS algorithms for perfect and imperfect periodic excitation sequences. The most interesting aspect of these algorithms is that they are exact LMS and RLS algorithms suitable for identification and tracking of every linear system and they require a real-time computational effort of just a multiplication, an addition and a subtraction per sample time. Moreover, the algorithms have convergence and tracking properties that can be better than or comparable with the NLMS algorithm for white noise input. The transient and steady state behavior of the algorithms and their tracking properties are also studied in the paper.nonemixedCarini, A
Tracking analysis of the normalized least mean square (NLMS) algorithm is carried out in the presenc...
Abstract—We propose a method for constructing optimal causal approximate inverse for discrete-time s...
summary:In this paper, the problem of obtaining a periodic model in state-space form of a linear pro...
The paper discusses computationally efficient NLMS and RLS algorithms for perfect and imperfect peri...
The paper discusses a novel sub-class of linear-in-the-parameters nonlinear filters, the Legendre no...
Filtered-x Least Mean Squares (FXLMS) algorithm is a well-known method for adapting feedforward FIR ...
The analysis of the Filtered-x Least Mean Square (FxLMS) algorithm can be based either on a stochast...
2We consider the identification of nonlinear filters using periodic sequences. Perfect periodic sequ...
In recent years, many new algorithms have been developed for detection of periodic patterns in symbo...
In this paper, the average mean square deviation (MSD) analysis of the normalized least mean square ...
Linear periodic systems originate in various control fields involving periodic phenomena. In the beg...
This paper addresses the fundamental problem of multi-channel system identification given the multip...
a state of the art survey of computational methods for periodic systems has been presented (Varga an...
3The paper introduces a novel family of deterministic signals, the orthogonal periodic sequences (OP...
International audienceIn this paper, the problem of inputreconstruction for the general case of peri...
Tracking analysis of the normalized least mean square (NLMS) algorithm is carried out in the presenc...
Abstract—We propose a method for constructing optimal causal approximate inverse for discrete-time s...
summary:In this paper, the problem of obtaining a periodic model in state-space form of a linear pro...
The paper discusses computationally efficient NLMS and RLS algorithms for perfect and imperfect peri...
The paper discusses a novel sub-class of linear-in-the-parameters nonlinear filters, the Legendre no...
Filtered-x Least Mean Squares (FXLMS) algorithm is a well-known method for adapting feedforward FIR ...
The analysis of the Filtered-x Least Mean Square (FxLMS) algorithm can be based either on a stochast...
2We consider the identification of nonlinear filters using periodic sequences. Perfect periodic sequ...
In recent years, many new algorithms have been developed for detection of periodic patterns in symbo...
In this paper, the average mean square deviation (MSD) analysis of the normalized least mean square ...
Linear periodic systems originate in various control fields involving periodic phenomena. In the beg...
This paper addresses the fundamental problem of multi-channel system identification given the multip...
a state of the art survey of computational methods for periodic systems has been presented (Varga an...
3The paper introduces a novel family of deterministic signals, the orthogonal periodic sequences (OP...
International audienceIn this paper, the problem of inputreconstruction for the general case of peri...
Tracking analysis of the normalized least mean square (NLMS) algorithm is carried out in the presenc...
Abstract—We propose a method for constructing optimal causal approximate inverse for discrete-time s...
summary:In this paper, the problem of obtaining a periodic model in state-space form of a linear pro...