Basics
Adaptive Resonance Theory
This network was developed by Stephen Grossberg and Gail Carpenter in 1987. It is based on competition and…
July 15, 2021 · Rajil TLBasics
Basics
Learning Vector Quantization
Learning Vector Quantization (LVQ), different from Vector quantization (VQ) and Kohonen Self-Organizing Maps (KSOM), basically is a competitive…
July 15, 2021 · Rajil TLBasics
Unsupervised Learning
As the name suggests, this type of learning is done without the supervision of a teacher. This learning…
July 15, 2021 · Rajil TLBasics
Supervised Learning
As the name suggests, supervised learning takes place under the supervision of a teacher. This learning process is dependent. During…
July 15, 2021 · Rajil TLBasics
Learning and Adaptation
As stated earlier, ANN is completely inspired by the way biological nervous system, i.e. the human brain works.…
July 15, 2021 · Rajil TLBasics
Artificial Neural Network – Building Blocks
Processing of ANN depends upon the following three building blocks − Network Topology Adjustments of Weights or Learning…
July 15, 2021 · Rajil TLBasics
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…
July 15, 2021 · Rajil TLBasics
Distributed Reasoning
Introduction There are many reasons why we might want to implement or adopt a distributed approach to reasoning…
July 15, 2021 · Rajil TLBasics
Bayesian networks
These are also called Belief Networks or Probabilistic Inference Networks. Initially developed by Pearl (1988). The basic idea is: Knowledge in…
July 15, 2021 · Rajil TLBasics
Dempster-Shafer Models
This can be regarded as a more general approach to representing uncertainty than the Bayesian approach. Bayesian methods…
July 15, 2021 · Rajil TL