Artificial Neural Network – Genetic Algorithm, Nature has always been a great source of inspiration to all mankind. Genetic Algorithms (GAs) are search-based algorithms based on the concepts of natural selec…Read More
Applications of Neural Networks, Before studying the fields where ANN has been used extensively, we need to understand why ANN would be the preferred choice of application.…Read More
Brain-State-in-a-Box Network, The Brain-State-in-a-Box (BSB) neural network is a nonlinear auto-associative neural network and can be extended to hetero-association with two or more layers. …Read More
Optimization Using Hopfield Network, Optimization is an action of making something such as design, situation, resource, and system as effective as possible. Using a resemblance between the cost fun…Read More
Other Optimization Techniques, Gradient descent, also known as the steepest descent, is an iterative optimization algorithm to find a local minimum of a function. While minimizing the functio…Read More
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…Read More
Boltzmann Machine, These are stochastic learning processes having recurrent structure and are the basis of the early optimization techniques used in ANN. Boltzmann Machine was inv…Read More
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 …Read More
Learning Vector Quantization, Learning Vector Quantization (LVQ), different from Vector quantization (VQ) and Kohonen Self-Organizing Maps (KSOM), basically is a competitive network which us…Read More
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 …Read More