The problem of clustering data can be formulated as a graph partitioning problem. In this setting, spectral methods for obtaining optimal solutions have received a lot of attention recently. We describe Perron Cluster Cluster Analysis (PCCA) and establish a connection to spectral graph partitioning. We show that in our approach a clustering can be efficiently computed by mapping the eigenvector...

A neuron can emit spikes in an irregular time basis and by averaging over a certain time window one would ignore a lot of information. It is known that in the context of fast information processing there is no sufficient time to sample an average firing rate of the spiking neurons. The present work shows that the spiking neurons are capable of computing the radial basis functions by storing the...

Now days, finding the association rule from large number of item-set become very popular issue in the field of data mining. To determine the association rule researchers implemented a lot of algorithms and techniques. FPGrowth is a very fast algorithm for finding frequent item-set. This paper, give us a new idea in this field. It replaces the role of frequent item-set to frequent sub graph disc...

A neuron can emit spikes in an irregular time basis and by averaging over a certain time window one would ignore a lot of information. It is known that in the context of fast information processing there is no sufficient time to sample an average firing rate of the spiking neurons. The present work shows that the spiking neurons are capable of computing the radial basis functions by storing the...

Microarray technology allows the measurement of expression levels of thousands of genes simultaneously and is expected to contribute significantly to advances in fundamental questions of biology and medicine. While microarrays monitor thousands of genes, there is a lot of evidence that only a few underlying signature components of gene subsets account for nearly all of the outcome variation. He...

The random graph of Erdős and Rényi is one of the oldest and best studied models of a network, and possesses the considerable advantage of being exactly solvable for many of its average properties. However, as a model of real-world networks such as the Internet, social networks or biological networks it leaves a lot to be desired. In particular, it differs from real networks in two crucial ways...

Abstract—As of today, the ability of providing personalized user experience has been a critical factor to determine whether a company can be successful or not. Then both academic and industry have devoted a lot of energy to promoting its development. In this paper, with the purpose of generating recommendation ranked lists, we put forward a new recommender scheme based on item clustering and ma...

In floorplan design it is useful to allow users to specify some placement constraints in the final packing. Clustering constraint is a popular type of placement constraint in which a given set of modules are restricted to be placed adjacent to one another. The wiring cost can be reduced by placing modules with a lot of interconnections closely together. Designers may also need this type of cons...

Fuzzy control systems and neural-network control systems for backing up a simulated truck, and truck-and-trailer, to a loading dock in a parking lot are presented. The supervised backpropagation learning algorithm trained the neural network systems. The robustness of the neural systems was tested by removing random subsets of training data in learning sequences. The neural systems performed wel...

Clustering has been proved to be an effective approach to organizing the wireless sensor network into a connected hierarchy for routing of sensing data. For efficient constructing in the actual circumstance, the distributed algorithm is more practical than the centralized algorithm. However, the distributed algorithm can not guarantee even distribution of cluster heads over the network, and it ...