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A Previously traditional methods were sufficient to protect the information, since it is simplicity in the past does not need complicated methods but with the progress of information technology, it become easy to attack systems, and detection of hiding methods became necessary to find ways parallel with the differing methods used by hackers, so the embedding methods could be under surveillance from...
This paper addresses the data-aided signal-to-noise ratio (SNR) estimation in time-variant flat Rayleigh fading channels. The time-variant fading channel is modeled by considering the Jakes' model and the first order autoregressive (AR1) model. Closed-form expressions of the Cramér-Rao bound (CRB) for data-aided SNR estimation are derived for fast and slow fading Rayleigh channels. As a special case,...
Novel higher order polynomial neural network architecture is presented in this paper. The new proposed neural network is called dynamic ridge polynomial neural network that combines the properties of higher order and recurrent neural networks. The advantage of this type of network is that it exploits the properties of higher-order neural networks by functionally extending the input space into a higher...
The use of neural networks as a nonlinear predictor in many applications including predictive image coding has been successfully presented by many researchers. However, almost all of the research papers have focused on the architecture of the neural network and very little attention has been given to the design of the training and testing data. This paper demonstrates how the choice of the training...
This paper presents a novel application of the self-organised multilayer perceptrons inspired by the immune algorithm in financial time series prediction. The simulation results were compared with the multilayer perceptrons and the functional link neural networks. The prediction capability of the various neural networks was tested on ten different data sets; the US/UK exchange rates, the JP/US exchange...
Self-healing in systems is one of the main characteristics of Autonomic Computing (AC). In this regard the challenge is how to implement self-healing systems in real time, since online learning is required so that the running system is tuned and adapted automatically, based on the current changes of the system's behavior. In this paper, to overcome the challenges associated with self-healing comprising...
This paper presents the classification of benign and malignant breast tumor based on fine needle aspiration cytology (FNAC) and probabilistic neural network (PNN). Five hundred and sixty nine sets of cell nuclei characteristics obtained by applying image analysis techniques to microscopic slides of FNAC samples of breast biopsy have been used in this study. These data were obtained from the University...
In this paper, we present an intelligent approach to analysing prostrate ultrasound images in order to diagnose prostate cancer. Algorithms based on fuzzy image processing are applied first to enhance the contrast of the original image, to extract the region of interest and to enhance the edges surrounding that region. Then, we extract features characterising the underlying texture of the regions...
This work mainly focuses on developing a concept towards building an object-centric thermal mapping (OCT Map) environment based on the use of wireless sensor networks. The sensor network is represented through infrastructural sensors of any functional space like the cool-room or a food-store. These sensors facilitate initial values for the calculation of the temperature at a given location within...
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