Feedforward Neural Network

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What Does Feedforward Neural Network Mean?

The feedforward neural network is a specific type of early artificial neural network known for its simplicity of design. The feedforward neural network has an input layer, hidden layers and an output layer. Information always travels in one direction – from the input layer to the output layer – and never goes backward.

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Techopedia Explains Feedforward Neural Network

The feedforward neural network, as a primary example of neural network design, has a limited architecture. Signals go from an input layer to additional layers. Some examples of feedforward designs are even simpler. For example, a single-layer perceptron model has only one layer, with a feedforward signal moving from a layer to an individual node. Multi-layer perceptron models, with more layers, are also feedforward.

In the days since scientists devised the first artificial neural networks, the technology world has made all sorts of progress in building more sophisticated models. There are recurrent neural networks and other designs that contain loops or cycles. There are models that involve backpropagation, where the machine learning system essentially optimizes by sending data back through a system. The feedforward neural network does not involve any of this type of design, and so it is a unique type of system that is good for learning these designs for the first time.

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Margaret Rouse
Technology Expert
Margaret Rouse
Technology Expert

Margaret is an award-winning technical writer and teacher known for her ability to explain complex technical subjects to a non-technical business audience. Over the past twenty years, her IT definitions have been published by Que in an encyclopedia of technology terms and cited in articles by the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine, and Discovery Magazine. She joined Techopedia in 2011. Margaret's idea of a fun day is helping IT and business professionals learn to speak each other’s highly specialized languages.