this paper presents the application of radial basis neural networks to the development of a novel method for the condition monitoring and fault diagnosis of synchronous generators. in the proposed scheme, flux linkage analysis is used to reach a decision. probabilistic neural network (pnn) and discrete wavelet transform (dwt) are used in design of fault diagnosis system. pnn as main part of thi...

Human natural killer-1 (HNK-1) carbohydrate (HSO3-3GlcAβ1-3Galβ1-4GlcNAc-R) is highly expressed in the brain and required for learning and neural plasticity. We previously demonstrated that expression of the HNK-1 epitope is mostly abolished in knockout mice for GlcAT-P (B3gat1), a major glucuronyltransferase required for HNK-1 biosynthesis, but remained in specific regions such as perineuronal...

Synapses are specialized structures that mediate rapid and efficient signal transmission between neurons and are surrounded by glial cells. Astrocytes develop an intimate association with synapses in the central nervous system (CNS) and contribute to the regulation of ion and neurotransmitter concentrations. Together with neurons, they shape intercellular space to provide a stable milieu for ne...

Abstract Machine learning is playing an increasing role in the physical sciences and significant progress has been made towards embedding domain knowledge into models. Less explored its use to discover interpretable laws from data. We propose parsimonious neural networks (PNNs) that combine with evolutionary optimization find models balance accuracy parsimony. The power versatility of approach ...

Article history: Received 1 August 2011 Available online 10 August 2011 Transmission Network Expansion Planning (TNEP) is a basic part of power network planning that determines where, when and how many new transmission lines should be added to the network. So, the TNEP is an optimization problem in which the expansion purposes are optimized. Artificial Intelligence (AI) tools such as Genetic Al...

In this paper, we introduce the architecture of Genetic Algorithm (GA) based Feed-forward Polynomial Neural Networks (PNNs) and discuss a comprehensive design methodology. A conventional PNN consists of Polynomial Neurons, or nodes, located in several layers through a network growth process. In order to generate structurally optimized PNNs, a GA-based design procedure for each layer of the PNN ...

Application of Polynomial Neural Networks( PNN) in mobile robot path planning with an obstacle avoidance scheme is proposed. Given an environment and a desired goal location (position and and orientation), PNN’s are built from some selected starting locations to reach this goal. These PNNs comprise the meniory of our model. An efficient associative retrieval technique is then applied to make th...

Throughout life animals learn to recognize cues that signal danger and instantaneously initiate an adequate threat response. Memories of such associations may last a lifetime and far outlast the intracellular molecules currently found to be important for memory processing. The memory engram may be supported by other more stable molecular components, such as the extracellular matrix structure of...