In this paper we explore the concept of sequential learning and the efficacy of global and local neural network learning algorithms on a sequential learning task. Pseudorehearsal (a method developed by Robins [19] to solve the catastrophic forgetting problem which arises from the excessive plasticity of neural networks) is significantly more effective than other local learning algorithms for th...

Recent studies have focused on developing security systems using micro-Doppler radars to detect human bodies. However, the resolution of these conventional methods is unsuitable for identifying bodies and moreover, most of these conventional methods were designed for a solitary or sufficiently well-spaced targets. This paper proposes a solution to these problems with an image separation method ...

A neural model for temporal pattern generation is used and analyzed for training with multiple complex sequences in a sequential manner. The network exhibits some degree of interference when new sequences are acquired. It is proven that the model is capable of incrementally learning a finite number of complex sequences. The model is then evaluated with a large set of highly correlated sequences...

Noise is source of ambiguity for fuzzy systems. Although being an important aspect, the effects of noise in fuzzy modeling have been little investigated. This paper presents a set of tests using three well-known fuzzy modeling algorithms. These evaluate perturbations in the extracted rule-bases caused by noise polluting the learning data, and the corresponding deformations in each learned funct...

A mobile-satellite system can utilize a wide variety of channels in order to provide services that fulfil various communication needs of aircraft, ship or land mobile earth stations. Network control data, facsimile, video and voice communications channels may be provided. The performance and link characteristics associated with these channels may differ and consequently, the tolerance of each c...

To make up the shortages of the existing vision navigation algorithms such as the noise interference and the processing speed, a new approach for navigation line detection is presented in this article. This new method was based on image boundary detection. The color images were transformed into binary ones after pre-processing. Then, three stages in this method were presented. At first, the ima...

Virtualization technology plays an essential role in resource in modern large data centers while it also causes interference among virtual machines which co-located in common physical machine contending for the shared physical resources. In this paper, we study the performance prediction models in virtualized environment. Unclassified model developed from all types of applications is quite inac...

Analysis and Survey of Issues in Live Virtual Machine Migration Interferences Ms. Tarannum Bloch Ph.D. Research Scholar, Faculty of Computer Science & Engineering, RDI Centre, C. U. Shah University, Wadhwan, Gujarat, India Dr. R Sridaran Dean, Faculty of Computer Applications, Marwadi Education Foundation Group of Institutions, Rajkot, Gujarat, India Dr. Prashanth CSR Head of Department (CSE), ...

Resource allocation for secondary users is an important issue in cognitive radio networks. In our article, we introduce a resource allocation scheme for secondary users to share spectrum in a cognitive radio network. Secondary users can exploit the spectrum owned by primary links when the interference level does not exceed certain requirements. Uncertainties of channel gains pose a great impact...

High-Tc superconducting quantum interference device (SQUID) is an ultra-sensitive magnetic sensor. After the discovery of the high-Tc superconducting materials, the performance of the high-Tc SQUID has been improved and stabilized. One strong candidate for application is a detection system of magnetic foreign matters in industrial products. There is a possibility that ultra-small metallic forei...