artificial neural network

More recently, Artificial neural network are being looked at as an alternative approach.

Artificial neural networks are a special type of computer processor.

It can be considered as a complex valued artificial neural network.

Some other recent work has used artificial neural networks with a hidden layer.

Before 1989, artificial neural networks have been used to model certain aspects of creativity.

Some of the most successful deep learning methods involve artificial neural networks.

Within the department, he is guiding the data mining and artificial neural networks group.

Artificial neural networks have also been used to diagnose several cancers.

Artificial neural networks in policy research: A current assessment.

These connections are, unlike most artificial neural networks, sparse and usually specific.

His work centred on the modelling capability of artificial neural networks.

By trying to make artificial neural networks that learn, perceive and remember, they hope to gain new insights into how people think.

There is no single formal definition of what an artificial neural network is.

Artificial neural networks are used extensively in such applications.

An example of a black box model is an artificial neural network since the explanation for the results is difficult to understand.

Oja is a prominent scientist in the area of artificial neural networks.

The probabilities are combined using an artificial neural network.

Lunt proposed adding an Artificial neural network as a third component.

But that's where artificial neural networks come in !

The basic components of artificial neural networks are nodes/units and weights.

Gaussian functions are used to define some types of artificial neural networks.

In the late 1980s, backgammon programmers found more success with an approach based on artificial neural networks.

That requires an enormously large computer or artificial neural network in comparison with today's super-computers.

An auto-encoder is an artificial neural network used for learning efficient codings.

It is based on evolving an artificial neural network through a discrete, infinite succession of states.