Intelligent System for Controlling a Three-Phase Active Filter
The nonlinear elements contained by electrothermal installation lead to three main negative effects, which are reflected in the power quality: circulation of reactive power, appearance of harmonic currents and unbalance…
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. Why Artificial Neural Networks? We need to…
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 selection and genetics. GAs are a…
Other Optimization Techniques
Iterated Gradient Descent Technique Gradient descent, also known as the steepest descent, is an iterative optimization algorithm to find a local minimum of a function. While minimizing the function, we…
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 function and energy function, we can…
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. It is also similar to Hopfield network. It…
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 invented by Geoffrey Hinton and Terry Sejnowski…
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…
