Add to ORKGThis paper presents a time-delayed neural network (TDNN) model that has the capability of learning and predicting the dynamic behavior of nonlinear elements that compose a wireless communication system. This model could help speeding up system deployment by reducing modeling time. This paper presents results of effective application of the TDNN model to an amplifier, part of a wireless transmitter.IFIP International Conference on Artificial Intelligence in Theory and Practice - Neural NetsRed de Universidades con Carreras en Informática (RedUNCI
This paper presents a black-box model that can be applied to characterize the nonlinear dynamic beha...
are applied to modeling of electronic circuits. ANNs are used for application of the black-box model...
This paper presents a new control model, ideal for teleoperation, which takes into account the probl...
This paper presents a time-delayed neural network (TDNN) model that has the capability of learning a...
In this paper, a novel carrier frequencydependent time delay neural network (CF-dependent TDNN) mode...
This paper presents a free software tool that supports the next-generation Mobile Communications, th...
International audienceThe design of telecommunication systems is a hierarchical process involving us...
A new Mixture of Experts Neural Network (ME-NN) approach is described and proposed for modeling of n...
Non-linearity of wireless transceivers, specifically power amplifier (PA) non-linearity, could pose ...
Complexity of RF designs in a wireless system continues to increase significantly, to support multip...
This paper represents a neural network based joint mitigation of the IQ imbalance and power amplifie...
Tracking the nonlinear behavior of an RF power amplifier (PA) is challenging. To tackle this problem...
technologies based on Neural Networks approach is proposed for modeling nonlinear memoryless communi...
This paper presents a black-box model that can be applied to characterize the nonlinear dynamic beha...
This paper presents a new approach to build RF dynamic behavioral models, based on time-delay neural...
This paper presents a black-box model that can be applied to characterize the nonlinear dynamic beha...
are applied to modeling of electronic circuits. ANNs are used for application of the black-box model...
This paper presents a new control model, ideal for teleoperation, which takes into account the probl...
This paper presents a time-delayed neural network (TDNN) model that has the capability of learning a...
In this paper, a novel carrier frequencydependent time delay neural network (CF-dependent TDNN) mode...
This paper presents a free software tool that supports the next-generation Mobile Communications, th...
International audienceThe design of telecommunication systems is a hierarchical process involving us...
A new Mixture of Experts Neural Network (ME-NN) approach is described and proposed for modeling of n...
Non-linearity of wireless transceivers, specifically power amplifier (PA) non-linearity, could pose ...
Complexity of RF designs in a wireless system continues to increase significantly, to support multip...
This paper represents a neural network based joint mitigation of the IQ imbalance and power amplifie...
Tracking the nonlinear behavior of an RF power amplifier (PA) is challenging. To tackle this problem...
technologies based on Neural Networks approach is proposed for modeling nonlinear memoryless communi...
This paper presents a black-box model that can be applied to characterize the nonlinear dynamic beha...
This paper presents a new approach to build RF dynamic behavioral models, based on time-delay neural...
This paper presents a black-box model that can be applied to characterize the nonlinear dynamic beha...
are applied to modeling of electronic circuits. ANNs are used for application of the black-box model...
This paper presents a new control model, ideal for teleoperation, which takes into account the probl...