Generally, the resolution of a problem by using soft-computing support requires several attempts for setting up a proper neural network. Such attempts consist of designing and training a neural network and can be a relevant effort for the developer. This paper proposes a toolbox that automates several steps for setting up a neural network, and provides high-level abstractions allowing a developer to choose classical network topologies and configure them as desired, as well as design a neural network from a scratch. A valuable aspect of our solution is given by the modularity of the whole design that builds on object-orientation and design patterns
The aim of this thesis is to explain and practically show the operation of different types of neural...
Neural network models are more often used in desktop applications given the increasing speed of comp...
A technique has been devised and tested which allows separate training of neural network (NN) module...
The aim of this report is to present an object-oriented approach to the design of a neural network s...
We present an object oriented environment for the design of neural network applications. The environ...
Article presents method of implementation of artificial neural network system by taking advantage o...
NEURObjects is a set of C++ library classes for neural network development, exploiting the potential...
Neural networks have been used to solve a wide range of problems. Unfortunately, many of the applica...
In dealing with complex problems, a monolithic neural network often becomes too large and complex to...
The field of software simulators for neural networks has been ex-panding very rapidly in the last ye...
Design research has demonstrated that neural networks are able to support creativity. However, there...
This paper presents a method for designing artificial neural network architectures. The method impli...
This thesis presents a study of neural network representation and behaviour. The study places neural...
Interest in artificial neural networks has grown rapidly over the past few years. The technology is ...
The popular multi-layer perceptron (MLP) topology with an error-back propagation learning rule doesn...
The aim of this thesis is to explain and practically show the operation of different types of neural...
Neural network models are more often used in desktop applications given the increasing speed of comp...
A technique has been devised and tested which allows separate training of neural network (NN) module...
The aim of this report is to present an object-oriented approach to the design of a neural network s...
We present an object oriented environment for the design of neural network applications. The environ...
Article presents method of implementation of artificial neural network system by taking advantage o...
NEURObjects is a set of C++ library classes for neural network development, exploiting the potential...
Neural networks have been used to solve a wide range of problems. Unfortunately, many of the applica...
In dealing with complex problems, a monolithic neural network often becomes too large and complex to...
The field of software simulators for neural networks has been ex-panding very rapidly in the last ye...
Design research has demonstrated that neural networks are able to support creativity. However, there...
This paper presents a method for designing artificial neural network architectures. The method impli...
This thesis presents a study of neural network representation and behaviour. The study places neural...
Interest in artificial neural networks has grown rapidly over the past few years. The technology is ...
The popular multi-layer perceptron (MLP) topology with an error-back propagation learning rule doesn...
The aim of this thesis is to explain and practically show the operation of different types of neural...
Neural network models are more often used in desktop applications given the increasing speed of comp...
A technique has been devised and tested which allows separate training of neural network (NN) module...