A quick gradient training algorithm for a specific neural network structure called an extra reduced size lattice-ladder multilayer perceptron is introduced. Presented derivation of the algorithm utilizes recently found by author simplest way of exact computation of gradients for rotation parameters of lattice-ladder filter. Developed neural network training algorithm is optimal in terms of minimal number of constants, multiplication and addition operations, while the regularity of the structure is also preserved
A new training algorithm is presented as a fast alternative to the backpropagation method. The new a...
Abstract—A new efficient computational technique for training of multilayer feedforward neural netwo...
Training a multilayer perceptron by an error backpropagation algorithm is slow and uncertain. This p...
A quick gradient training algorithm for a specific neural network structure called an extra reduced ...
A lattice-ladder multilayer perceptron (LLMLP) is an appealing structure for advanced signal process...
The perceptron is essentially an adaptive linear combiner with the output quantized to ...
Abstract- We propose a novel learning algorithm to train networks with multi-layer linear-threshold ...
The natural gradient descent method is applied to train an n-m-1 mul-tilayer perceptron. Based on an...
The multilayer perceptron is one of the most commonly used types of feedforward neural networks and ...
The use of multilayer perceptrons (MLP) with threshold functions (binary step function activations) ...
The speed of convergence while training is an important consideration in the use of neural nets. The...
This paper presents two compensation methods for multilayer perceptrons (MLPs) which are very diffic...
This paper presents a method based on evolutionary com-putation to train multilayer morphological pe...
We present a training algorithm for multilayer perceptrons which relates to the technique of princip...
Several neural network architectures have been developed over the past several years. One of the mos...
A new training algorithm is presented as a fast alternative to the backpropagation method. The new a...
Abstract—A new efficient computational technique for training of multilayer feedforward neural netwo...
Training a multilayer perceptron by an error backpropagation algorithm is slow and uncertain. This p...
A quick gradient training algorithm for a specific neural network structure called an extra reduced ...
A lattice-ladder multilayer perceptron (LLMLP) is an appealing structure for advanced signal process...
The perceptron is essentially an adaptive linear combiner with the output quantized to ...
Abstract- We propose a novel learning algorithm to train networks with multi-layer linear-threshold ...
The natural gradient descent method is applied to train an n-m-1 mul-tilayer perceptron. Based on an...
The multilayer perceptron is one of the most commonly used types of feedforward neural networks and ...
The use of multilayer perceptrons (MLP) with threshold functions (binary step function activations) ...
The speed of convergence while training is an important consideration in the use of neural nets. The...
This paper presents two compensation methods for multilayer perceptrons (MLPs) which are very diffic...
This paper presents a method based on evolutionary com-putation to train multilayer morphological pe...
We present a training algorithm for multilayer perceptrons which relates to the technique of princip...
Several neural network architectures have been developed over the past several years. One of the mos...
A new training algorithm is presented as a fast alternative to the backpropagation method. The new a...
Abstract—A new efficient computational technique for training of multilayer feedforward neural netwo...
Training a multilayer perceptron by an error backpropagation algorithm is slow and uncertain. This p...