Add to ORKGRecursive Least Squares (RLS) are adaptive filters that search for the coefficient weights that are set to minimize the weighted linear least square cost function of the signal that is inputted. In the RLS derivation, the input signals are known to be deterministic. This method provides fast convergence but its drawback is the high cost of computational complexity. On the other hand, the Least Means Square algorithm is used to mimic the desired filter by searching for its filter coefficients which relate to producing the least means square of the error signal. This method uses a stochastic gradient descent method in the filter. This research will develop a Recursive Least Square and Least Means Square Equalizers Optimization Algorithms in R...
The major problems in today\u27s wireless communications is time dispersion and inter symbol interfe...
daptive filters are used for non-stationary signals and environments, or in applications where a sam...
The error rate performance of a previously developed reduced complexity channel estimator, known as ...
Recursive Least Squares (RLS) are adaptive filters that search for the coefficient weights that are ...
The Recursive Least Squares algorithm (RLS) is utilized in digital signal processing as an adaptive ...
This paper is intended to analyse the performance, the rate of convergence, selection of proper filt...
Inter-symbol interference if not taken care off may cause severe error at the receiver and the detec...
In this paper, we present the experiment results of three adaptive equalization algorithms: least-me...
Adaptive filters can be used for channel equalization and estimation. When a signal goes through an ...
This paper proposes a new fast recursive total least squares (N-RTLS) algorithm to recursively compu...
The paper presents a new family of RLS adaptive filter-ing algorithms developed for non-stationary s...
In this paper, research on exploring the potential of several popular equalization techniques while ...
[[abstract]]The environment of the communication system will be more complicated in the future. Ther...
One of the most important issues in the area of digital signal processing is a signal noise cancella...
Abstract—Decision Feedback Equalizers (DFE) are used to eliminate the effect of Inter Symbol Interfe...
The major problems in today\u27s wireless communications is time dispersion and inter symbol interfe...
daptive filters are used for non-stationary signals and environments, or in applications where a sam...
The error rate performance of a previously developed reduced complexity channel estimator, known as ...
Recursive Least Squares (RLS) are adaptive filters that search for the coefficient weights that are ...
The Recursive Least Squares algorithm (RLS) is utilized in digital signal processing as an adaptive ...
This paper is intended to analyse the performance, the rate of convergence, selection of proper filt...
Inter-symbol interference if not taken care off may cause severe error at the receiver and the detec...
In this paper, we present the experiment results of three adaptive equalization algorithms: least-me...
Adaptive filters can be used for channel equalization and estimation. When a signal goes through an ...
This paper proposes a new fast recursive total least squares (N-RTLS) algorithm to recursively compu...
The paper presents a new family of RLS adaptive filter-ing algorithms developed for non-stationary s...
In this paper, research on exploring the potential of several popular equalization techniques while ...
[[abstract]]The environment of the communication system will be more complicated in the future. Ther...
One of the most important issues in the area of digital signal processing is a signal noise cancella...
Abstract—Decision Feedback Equalizers (DFE) are used to eliminate the effect of Inter Symbol Interfe...
The major problems in today\u27s wireless communications is time dispersion and inter symbol interfe...
daptive filters are used for non-stationary signals and environments, or in applications where a sam...
The error rate performance of a previously developed reduced complexity channel estimator, known as ...