this paper extends the sequential learning algorithm strategy of two different types of adaptive radial basis function-based (rbf) neural networks, i.e. growing and pruning radial basis function (gap-rbf) and minimal resource allocation network (mran) to cater for on-line identification of non-linear systems. the original sequential learning algorithm is based on the repetitive utilization of s...

previous studies have shown that morphine administration could inhibit neural tube development in rat embryos and produce behavioral defects in human and animals. in the present study, the effects of maternal morphine consumption on embryonic neural plate development in wistar rats were investigated. methods: twenty-four female wistar rats (250-300 g) were crossed with males. after pregnancy, t...

multiple sclerosis (ms) and its animal model, experimental autoimmune encephalomyelitis (eae), are chronic inflammatory demyelinating disorders of central nervous system (cns). while the cause is unclear, the fundamental mechanism is thought to be destruction of myelin sheaths of neurons through immune system. one of the approaches being proposed in eae therapy is neural stem cells (nscs) trans...

In this paper we present an improved neural network to solve strictly convex quadratic programming(QP) problem. The proposed model is derived based on a piecewise equation correspond to optimality condition of convex (QP) problem and has a lower structure complexity respect to the other existing neural network model for solving such problems. In theoretical aspect, stability and global converge...

Routing is one of the basic parts of a message passing multiprocessor system. The routing procedure has a great impact on the efficiency of a system. Neural algorithms that are currently in use for computer networks require a large number of neurons. If a specific topology of a multiprocessor network is considered, the number of neurons can be reduced. In this paper a new recurrent neural ne...

Neural networks were used to estimate the cost of jet engine components, specifically shafts and cases. The neural network process was compared with results produced by the current conventional cost estimation software and linear regression methods. Due to the complex nature of the parts and the limited amount of information available, data expansion techniques such as doubling-data and data-cr...

this is the first attempt at process modeling in terms of predictive control using a hierachical method based on regression analysis and artificial neural networks (anns). this hierachical method leads to the reliability improvement of neural model of the process in predicting (extrapolation and interpolation) the process output. such an outlook makes it possible to predict the proper input set...

this paper presents the application of three main artificial neural networks (anns) in damage detection of steel bridges. this method has the ability to indicate damage in structural elements due to a localized change of stiffness called damage zone. the changes in structural response is used to identify the states of structural damage. to circumvent the difficulty arising from the non-linear n...

Today for the expedition of the identification and timely correction of process deviations, it is necessary to use advanced techniques to minimize the costs of production of defective products. In this way control charts as one of the important tools for the statistical process control in combination with modern tools such as artificial neural networks have been used. The artificial neural netw...

security term in mobile ad hoc networks has several aspects because of the special specification of these networks. in this paper a distributed architecture was proposed in which each node performed intrusion detection based on its own and its neighbors’ data. fuzzy-neural interface was used that is the composition of learning ability of neural network and fuzzy ratiocination of fuzzy system as...