This work proposes a framework to determine the optimal Wiener equalizer by using an artificial immune network model together with the constant modulus (CM) cost function. This study was primarily motivated by recent theoretical results concerning the CM criterion and its relation to the Wiener approach. The proposed immune-based technique was tested under different channel models and filter orders, and benchmarked against a procedure using a genetic algorithm with niching. The results demonstrated that the proposed strategy has a clear superiority when compared with the more traditional technique. The proposed algorithm presents interesting features from the perspective of multimodal search, being capable of determining the optimal Wiener ...
New block-based blind equalization algorithms are introduced based upon the cost function underlying...
Adaptive channel equalization without resorting to a training sequence is often referred to as blind...
In this study, a modified Fuzzy C-Means algorithm with Gaussian weights (MFCM_GW) is presented for t...
The multimodal and time-varying aspects of blind equalization problems in communication systems are ...
Due to its universal approximation capability, the multilayer perceptron (MLP) neural network has be...
New blind adaptive channel equalization techniques based on a deterministic optimization criterion a...
In this work, we study the criteria used to solve the blind equalization problem. Two approaches are...
Abstract—In this work, we propose an evolutionary-like approach to the problem of blind adaptive spa...
Blind inversion of nonlinear systems is a complex task that requires some sort of prior information ...
This paper proposes a novel equalizer, termed here as Evolutionary MPNN, where a complex modified pr...
In many real-world scenarios, in contrast to standard benchmark optimization problems, we may face s...
A family of blind equalisation algorithms identifies a channel model based on a higher-order cumulan...
Another contribution is the proposal of an upper bound for the CM cost function based on the mean fo...
Abstract—An important family of blind equalization algorithms identify a communication channel model...
International audienceIn this paper, new decision directed algorithms for blind equalization of comm...
New block-based blind equalization algorithms are introduced based upon the cost function underlying...
Adaptive channel equalization without resorting to a training sequence is often referred to as blind...
In this study, a modified Fuzzy C-Means algorithm with Gaussian weights (MFCM_GW) is presented for t...
The multimodal and time-varying aspects of blind equalization problems in communication systems are ...
Due to its universal approximation capability, the multilayer perceptron (MLP) neural network has be...
New blind adaptive channel equalization techniques based on a deterministic optimization criterion a...
In this work, we study the criteria used to solve the blind equalization problem. Two approaches are...
Abstract—In this work, we propose an evolutionary-like approach to the problem of blind adaptive spa...
Blind inversion of nonlinear systems is a complex task that requires some sort of prior information ...
This paper proposes a novel equalizer, termed here as Evolutionary MPNN, where a complex modified pr...
In many real-world scenarios, in contrast to standard benchmark optimization problems, we may face s...
A family of blind equalisation algorithms identifies a channel model based on a higher-order cumulan...
Another contribution is the proposal of an upper bound for the CM cost function based on the mean fo...
Abstract—An important family of blind equalization algorithms identify a communication channel model...
International audienceIn this paper, new decision directed algorithms for blind equalization of comm...
New block-based blind equalization algorithms are introduced based upon the cost function underlying...
Adaptive channel equalization without resorting to a training sequence is often referred to as blind...
In this study, a modified Fuzzy C-Means algorithm with Gaussian weights (MFCM_GW) is presented for t...