Publication

Modular Object-Oriented Neural Network Simulators and Topology Generalizations

1994
Conference Papers

Abstract

A growing number of neural networks are based on topologies that deviate from the standard fixed first order fully interlayer connected ones. Although there currently exist a variety of neural network simulators, few are flexible enough to facilitate substantial topology alterations. Some novel modular object-oriented neural network simulators promise modifications and extensions to be made with minimal effort. Two of these simulators are described and compared: OpenSimulator (version 3.1) and Sesame (version 4.5). An extension of these simulators to high-order and ontogenic neural networks is outlined.

Official source

https://infoscience.epfl.ch/entities/publication/437f1b88-e06c-4f2c-8edb-623ab14b64ee

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1994
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/437f1b88-e06c-4f2c-8edb-623ab14b64ee

About this result

Related concepts (17)

Artificial neural network

Artificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.

Neural network

A neural network can refer to a neural circuit of biological neurons (sometimes also called a biological neural network), a network of artificial neurons or nodes in the case of an artificial neural network. Artificial neural networks are used for solving artificial intelligence (AI) problems; they model connections of biological neurons as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed.

Types of artificial neural networks

There are many types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate functions that are generally unknown. Particularly, they are inspired by the behaviour of neurons and the electrical signals they convey between input (such as from the eyes or nerve endings in the hand), processing, and output from the brain (such as reacting to light, touch, or heat). The way neurons semantically communicate is an area of ongoing research.

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Modular Object-Oriented Neural Network Simulators and Topology Generalizations

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