Artificial Neural Network – Hopfield Networks
Hopfield neural network was invented by Dr. John J. Hopfield in 1982. It consists of a single layer which contains one or more fully connected recurrent neurons. The Hopfield network…
Associate Memory Network
These kinds of neural networks work on the basis of pattern association, which means they can store different patterns and at the time of giving an output they can produce…
Kohonen Self-Organizing Feature Maps
Suppose we have some pattern of arbitrary dimensions, however, we need them in one dimension or two dimensions. Then the process of feature mapping would be very useful to convert…
Adaptive Resonance Theory
This network was developed by Stephen Grossberg and Gail Carpenter in 1987. It is based on competition and uses unsupervised learning model. Adaptive Resonance Theory (ART) networks, as the name…
Learning Vector Quantization
Learning Vector Quantization (LVQ), different from Vector quantization (VQ) and Kohonen Self-Organizing Maps (KSOM), basically is a competitive network which uses supervised learning. We may define it as a process…
Unsupervised Learning
As the name suggests, this type of learning is done without the supervision of a teacher. This learning process is independent. During the training of ANN under unsupervised learning, the…
Supervised Learning
As the name suggests, supervised learning takes place under the supervision of a teacher. This learning process is dependent. During the training of ANN under supervised learning, the input vector is presented…
Learning and Adaptation
As stated earlier, ANN is completely inspired by the way biological nervous system, i.e. the human brain works. The most impressive characteristic of the human brain is to learn, hence…
Artificial Neural Network – Building Blocks
Processing of ANN depends upon the following three building blocks − Network TopologyAdjustments of Weights or LearningActivation Functions In this chapter, we will discuss in detail about these three building…
Artificial Neural Network – Basic Concepts
Artificial neural networks (ANNs) or connectionist systems are computing systems inspired by the biological neural networks that constitute animal brains. Such systems learn (progressively improve performance) to do tasks by considering examples, generally without task-specific programming.…
