We derive a new criterion for checking the global stability of periodic oscillation of bidirectional associative memory BAM neural networks with periodic coefficients and distributed delay, and find that the criterion relies on the Lipschitz constants of the signal transmission functions, weights of the neural network, and delay kernels. The proposed model transforms the original interacting ne...

| We address pruning and evaluation of Tapped-Delay Neural Networks for the sunspot benchmark series. It is shown that the generalization ability of the networks can be improved by pruning using the Optimal Brain Damage method of Le Cun, Denker and Solla. A stop criterion for the pruning algorithm is formulated using a modiied version of Akaike's Final Prediction Error estimate. With the propos...

We consider critically loaded single class queueing networks with infinite buffers in which arrival and service rates are state (i.e., queue length) dependent and may be dynamically controlled. An optimal rate control problem for such networks with an ergodic cost criterion is studied. It is shown that the value function (i.e., optimum value of the cost) of the rate control problem for the netw...

The comparison of heterogeneous samples extensively exists in many applications, especially in the task of image classification. In this paper, we propose a simple but effective coupled neural network, called Deeply Coupled Autoencoder Networks (DCAN), which seeks to build two deep neural networks, coupled with each other in every corresponding layers. In DCAN, each deep structure is developed ...

The optimization of multicast communication for regular interconnection networks (INs) has been the subject of many studies in the literature. Extensions, however, the analysis of INs with arbitrary topology and background traffic poses a great challenge. In this context, a novel heuristic algorithm for multicast communication is proposed for arbitrary INs with finite capacity and bursty backgr...

The growth of fingerprint databases creates a need for strategies to reduce the identification time. Fingerprint classification reduces the search penetration rate by grouping the fingerprints into several classes. Typically, features describing the visual patterns of a fingerprint are extracted and fed to a classifier. The extraction can be time-consuming and error-prone, especially for finger...

An orthogonal forward selection (OFS) algorithm based on the leaveone-out (LOO) criterion is proposed for the construction of radial basis function (RBF) networks with tunable nodes. This OFS-LOO algorithm is computationally efficient and is capable of identifying parsimonious RBF networks that generalise well. Moreover, the proposed algorithm is fully automatic and the user does not need to sp...

A criterion for a three-stage network to be strictly non-blocking is presented which is very general in its application. The criterion distinguishes between channel grouping and link speedup as methods of increasing the bandwidth available to calls. It may be applied to both circuit-switched and packet-switched networks. The non-blocking conditions for various networks are shown to be special c...

We consider critically loaded single class queueing networks with infinite buffers in which arrival and service rates are state (i.e., queue length) dependent and may be dynamically controlled. An optimal rate control problem for such networks with an ergodic cost criterion is studied. It is shown that the value function (i.e., optimum value of the cost) of the rate control problem for the netw...

This paper studies optimal power allocation to minimize symbol error rate (SER) of amplify-and-forward cooperative diversity networks. First, we analytically solve optimal power allocation problem to minimize SER for three different scenarios, namely, multi-branch single-relay, single-branch multi-relay and multi-branch multi-relay cooperative diversity networks, all subject to a given total re...