BACKGROUND Sandhoff disease is an autosomal recessive disorder caused by β-hexosaminidase deficiency in which the ganglioside GM2 and other glycolipids accumulate intracellularly within lysosomes. This process results in progressive motor neuron manifestations, death from respiratory failure and infections in infantiles. CASE REPORT This report presents a 22-month-old girl with infantile type...

This paper considers a new class of additive neural networks where the neuron activations are modelled by discontinuous functions with nonlinear growth. By Leray-Schauder alternative theorem in differential inclusion theory, matrix theory, and generalized Lyapunov approach, a general result is derived which ensures the existence and global asymptotical stability of a unique periodic solution fo...

The concept of neural networks is generalized to include complex connect ions between complex units. A mathemat ical model is presented. An expression for the network's energy as well as a complex learning rule are proposed. Th is innovation may lead to new neural network paradigms, architectures, and applications, and may help to better understand biological nervous systems. The similarity bet...

in this paper we investigate generalized topologies generated by a subbase ofpreorder relators and consider its application in the concept of the complement. we introducethe notion of principal generalized topologies obtained from the new type of open sets andstudy some of their important properties.

Short Term Load Forecasting(STLF) varies from an hour to hour and is used for requirement for control, unit commitment, security assessment, optimum planning of power generation, and planning of both spinning reserve and energy exchange, also as inputs to load flow studies and contingency analysis. Artificial neural networks (ANN’s) has drawbacks like inputs nodes or hidden nodes which can caus...

VVei-Tsih Lee School of Electrical Engineering Purdue University VV. Lafayette, UN. 47907 [email protected] This work introduces a new method called Self Organizing Neural Network (SONN) algorithm and demonstrates its use in a system identification task. The algorithm constructs the network, chooses the neuron functions, and adjusts the weights. It is compared to the Back-Propagation algori...

In this paper, we investigate the almost periodic dynamical behaviors for a class of general Cohen–Grossberg neural networks with discontinuous right-hand sides, time-varying and distributed delays. By means of retarded differential inclusions theory and nonsmooth analysis theory with generalized Lyapunov approach, we obtain the existence, uniqueness and global stability of almost periodic solu...

A new algorithm for learning invariance manifolds is introduced that allows a neuron to learn a non-linear transfer function to extract invariant or rather slowly varying features from a vectorial input sequence. This is generalized to a group of neurons, referred to as a Gibson-clique, to learn slowly varying features that are uncorrelated. Since the transfer functions are non-linear, this tec...

Application of Artificial Neural Networks (ANNs) for electrical load forecasting has been proposed in the literature. ANNs have some inherent drawbacks and limitations, such as difficulty in deciding the structure of ANN, selection of type of neuron, large training time, sticking to local minima, etc. To overcome the drawbacks of ANN, a Generalized Neural Network (GNN) has been proposed in the ...

The artificial neural network is a popular framework in machine learning. To empower individual neurons, we recently suggested that the current type of neurons could be upgraded to second-order counterparts, in which the linear operation between inputs to a neuron and the associated weights is replaced with a nonlinear quadratic operation. A single second-order neurons already have a strong non...