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What are the basic components of artificial neural network? 

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Artificial neural networks (ANNs) are systems that can learn.

Although the working principles and simple set of rules of artificial neuron looks like nothing special the full potential and calculation power of these models come to life when we start to interconnect them into artificial neural networks (Figure 1) These artificial neural networks use simple fact that complexity can grown out of merely few basic and simple rules.

Such models provide the unique features of each components, the reasoning and explanation of expert system and the generalization and adaptability of artificial neural networks.

The network serves as a simple example of an artificial neural network with an adaptable modular structure.

The artificial neural network techniques are rather easy to develop and to perform.

The basic circuitry of this neural system is reasonably well understood, and can be modeled, to a first approximation, employing neural network principles.

Among these, the artificial neural network (NN) system appears to be a powerful tool to tackle situations in w...

These results provide new insights into how basic properties of artificial neural networks might be relevant for modeling neural information processing in biological systems.

The realization of various psychological functions in a single device simplifies the construction of the artificial neural network and facilitates the advent of artificial intelligence.