Multilayer perceptrons (MLPs) (1) are the most common artificial neural networks employed in a large field of applications. In control and signal processing applications, MLPs are mainly used as nonlinear mapping approximators. The most common training algorithm used with MLPs is the error back-propagation (BP) alg. (1)
In this contribution we present an algorithm for using possibly inaccurate knowledge of model deriva...
A new training algorithm is presented as a fast alternative to the backpropagation method. The new a...
Back Propagation (BP) was introduced by Rumelhart in 1986 [1]. BP is used for learning algorithm of ...
Multilayer perceptrons (MLPs) (1) are the most common artificial neural networks employed in a large...
Multilayer perceptrons (MLPs) (1) are the most common artificial neural networks employed in a large...
A multilayer perceptron is a feed forward artificial neural network model that maps sets of input da...
This paper presents two compensation methods for multilayer perceptrons (MLPs) which are very diffic...
Several neural network architectures have been developed over the past several years. One of the mos...
ABSTRACT A new fast training algorithm for the Multilayer Perceptron (MLP) is proposed. This new alg...
A adaptive back-propagation algorithm for multilayered feedforward perceptrons was discussed. It was...
We present a training algorithm for multilayer perceptrons which relates to the technique of princip...
The multilayer perceptron is one of the most commonly used types of feedforward neural networks and ...
Backpropagation algorithm is the most commonly used algorithm for training artificial neural network...
The Multi-Layer Perceptron (MLP) is one of the most widely applied and researched Artificial Neural ...
Abstract Recently back propagation neural network BPNN has been applied successfully in many areas w...
In this contribution we present an algorithm for using possibly inaccurate knowledge of model deriva...
A new training algorithm is presented as a fast alternative to the backpropagation method. The new a...
Back Propagation (BP) was introduced by Rumelhart in 1986 [1]. BP is used for learning algorithm of ...
Multilayer perceptrons (MLPs) (1) are the most common artificial neural networks employed in a large...
Multilayer perceptrons (MLPs) (1) are the most common artificial neural networks employed in a large...
A multilayer perceptron is a feed forward artificial neural network model that maps sets of input da...
This paper presents two compensation methods for multilayer perceptrons (MLPs) which are very diffic...
Several neural network architectures have been developed over the past several years. One of the mos...
ABSTRACT A new fast training algorithm for the Multilayer Perceptron (MLP) is proposed. This new alg...
A adaptive back-propagation algorithm for multilayered feedforward perceptrons was discussed. It was...
We present a training algorithm for multilayer perceptrons which relates to the technique of princip...
The multilayer perceptron is one of the most commonly used types of feedforward neural networks and ...
Backpropagation algorithm is the most commonly used algorithm for training artificial neural network...
The Multi-Layer Perceptron (MLP) is one of the most widely applied and researched Artificial Neural ...
Abstract Recently back propagation neural network BPNN has been applied successfully in many areas w...
In this contribution we present an algorithm for using possibly inaccurate knowledge of model deriva...
A new training algorithm is presented as a fast alternative to the backpropagation method. The new a...
Back Propagation (BP) was introduced by Rumelhart in 1986 [1]. BP is used for learning algorithm of ...