Conventional model-based data processing methods are computationally expensive and
require experts' knowledge for the modelling of a system. Neural networks are a model-free …

In some practical applications of neural networks, fast response to external events within an
extremely short time is highly demanded and expected. However, the extensively used …

Back propagation training algorithm is widely used techniques in artificial neural network
and is also very popular optimization task in finding an optimal weight sets during the …

Neural Networks: Computational Models and Applications covers a wealth of important
theoretical and practical issues in neural networks, including the learning algorithms of feed …

An accelerated hybrid learning algorithm is proposed for the training of fuzzy wavelet neural
networks (FWNNs). The algorithm gives the initial parameters by the clustering algorithm …

Automatic image segmentation of immunohistologically stained breast tissue sections helps
pathologists to discover the cancer disease earlier. The detection of the real number of …

An architecture, systems and methods for a scalable artificial neural network, wherein the
architecture includes: an input layer; at least one hidden layer; an output layer; and a …

Science has made great progress in the twentieth century, with the establishment of proper
disciplines in the fields of physics, computer science, molecular biology, and many others. At …

Feedforward neural networks (FNN) have been proposed to solve complex problems in
pattern recognition, classification and function approximation. Despite the general success …

Metaheuristic algorithms are popular techniques used to solve several optimization
problems. Among the key algorithms, cuckoo search (CS) is a comparatively novel and …