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Artificial neural networks (ANNs) are models created using machine learning to perform a number of tasks.Their creation was inspired by biological neural circuitry. [1] [a] While some of the computational implementations ANNs relate to earlier discoveries in mathematics, the first implementation of ANNs was by psychologist Frank Rosenblatt, who developed the perceptron. [1]
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ADALINE (Adaptive Linear Neuron or later Adaptive Linear Element) is an early single-layer artificial neural network and the name of the physical device that implemented it. [ 2 ] [ 3 ] [ 1 ] [ 4 ] [ 5 ] It was developed by professor Bernard Widrow and his doctoral student Marcian Hoff at Stanford University in 1960.
Giles' work on neural networks showed that fundamental computational structures such as regular grammars and finite state machines could be theoretically represented in recurrent neural networks. Another contribution was the Neural Network Pushdown Automata and the first analog differentiable stack. Some of these publications are cited as early ...
LeNet-5 architecture (overview). LeNet is a series of convolutional neural network structure proposed by LeCun et al. [1] The earliest version, LeNet-1, was trained in 1989.In general, when "LeNet" is referred to without a number, it refers to LeNet-5 (1998), the most well-known version.
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Emergent features a modular design, based on the principles of object-oriented programming.It runs on Microsoft Windows, Darwin / macOS and Linux.C-Super-Script (variously, CSS and C^C), a built-in C++-like interpreted scripting language, allows access to virtually all simulator objects and can initiate all the same actions as the GUI, and more.
In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains. [1] [2] An ANN consists of connected units or nodes called artificial neurons, which loosely model the neurons in the brain. Artificial ...