Neural Network World; International Journal on Neural and Mass - Parallel Computing and Information Systems

Self-Adaptive Parallel Processing Neural Networks with Irregular Nodal Processing Powers Using Hierarchical Partitioning

The architecture and working of the Artificial Neural Networks are an inspiration from the human brain. The brain due to its highly parallel nature and immense computational powers still remains the motivation for researchers. A single system-single processor approach is a highly unlikely way to model a neural network for large computational needs. Many approaches have been proposed that adopt a parallel implementation of ANNs. These methods do not consider the difference in processing powers...

Finding the Same Source Programs Based On the Structural Fingerprint Distance of Call Graph

With the purpose of guaranteeing the copyright and security of software, we introduce the structural fingerprint and the distance of the fingerprint to find the same source programs from a great deal of programs in this paper. In order to gain the structural fingerprint, the in-degree, out-degree and adjacency relationship are exacted from call graph to construct a structural matrix. Then this matrix is mapped to RGB image and to compute the color moments of this image. Comparing with the tra...

Performance Comparison of Six Efficient Pure Heuristics for Scheduling Meta-Tasks On Heterogeneous Distributed Environments

Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous distributed computing systems and represents an NP-complete problem. Therefore, using meta-heuristic algorithms is a suitable approach in order to cope with its difficulty. In many meta-heuristic algorithms, generating individuals in the initial step has an important effect on the convergence behavior of the algorithm and final solutions. Using some pure heuristics for generating one or more near-opti...

Tri-State Cascading Pulse Coupled Neural Network and Its Application in Finding Shortest Path

To increase the computing speed of neural networks by means of parallel performance, a new mode of neural network, named Tri-state Cascading Pulse Coupled Neural Network (TCPCNN), is presented in this paper, which takes the ideas of three-state and pipelining used in circuit designing into neural network, and creates new neuron with three states: sub-firing, firing and inhibition. The proposed model can transmit signals in parallel way, as it is inspired not only in the direction of auto-wave...

Finding the Path Centre of a Communications Network

The centre of a communications network is a vertex set. The distances between every vertex in the centre set and all other vertices of the network are minimal. In some cases, the centre of the network can be a path, which includes a desired number of vertices. This centre is called a path centre of the network. In this paper, we aim to find a path centre of a given network with the needed number of vertices. We give the distance measures of the network and represent an algorithm searching the...

Model of Mac Sub-Layer of a Can Protocol by Using Hierarchical Coloured Petri Net

This article presents a design of model of the medium access control (MAC) of a sub-layer of a Controller Area Network (CAN) protocol (CAN is the most widely used in-vehicle network). The model is created via hierarchical Coloured Petri Nets. For better clarity and comprehension, the wide created model is divided into submodules. An application CPN Tools, developed by the CPN group at the University of Aarhus (Denmark), is used as a modelling tool. This model expresses the whole CAN's fault c...