While the past century of neuroscientific research has brought considerable progress in defining the boundaries of the human cerebral cortex, there are cases in which the demarcation of one area from another remains fuzzy. Despite the existence of clearly demarcated areas, examples of gradual transitions between areas are known since early cytoarchitectonic studies. Since multi-modal anatomical...

Measures of network structural integrity useful in the analysis and synthesis of power systems are discussed. Signal flow methodology is applied to derive an expression for the paths between sources and sinks in a power network. Connectivity and reach ability properties of the network are obtained using the minors of a modified connectivity matrix. Node-connectivity, branch connectivity and mix...

In joining defects on semiconductor wafer maps into clusters, it is common for defects caused by different sources to overlap. Simple morphological image processing tends to either join too many unrelated defects together or not enough together. Expert semiconductor fabrication engineers have demonstrated that they can easily group clusters of defects from a common manufacturing problem source ...

In this paper a novel neuro-fuzzy system is proposed where its learning is based on the creation of fuzzy relations by using new implication method without utilizing any exact mathematical techniques. Then, a simple memristor crossbar-based analog circuit is designed to implement this neuro-fuzzy system which offers very interesting properties. In addition to high connectivity between neurons a...

Generalized modeling principles of a nonlinear system with a dynamic fuzzy network (DFN)a network with unconstrained connectivity and with dynamic fuzzy processing units called ‘feurons’, have been given. DFN model has been trained both in open loop and closed loop forms to satisfy these principles. Several system trajectories with a PRBS input have been used for open loop training. DFN model o...

– We use a Gaussian radial basis kernel function to map pairs of feature vectors from a sample into a fuzzy connectivity matrix whose entries are fuzzy truths that the vector pairs belong to the same classes. To reduce the matrix size when the data set is large, we obtain a smaller set of representative vectors to form a smaller matrix. To this end we first group the feature vectors into many s...

Magnetic Resonance Imaging (MRI) based brain cancer segmentation methods need the skull stripping algorithms as their pre-processing tool. Skull is challenged by less accuracy and high time consumption; hence, an effective method needed for medical world. In this research, a novel on MRI proposed, which named 'Skull Stripping in using FHECE enhancement, Fuzzy clustering Morphological operations...