Feel lonely? What about reading books? Book is one of the greatest friends to accompany while in your lonely time. When you have no friends and activities somewhere and sometimes, reading book can be a great choice. This is not only for spending the time, it will increase the knowledge. Of course the b=benefits to take will relate to what kind of book that you are reading. And now, we will conc...

In this paper, a key generation and certification technique using multilayer perceptron (KGCMLP) has been proposed in wireless communication of data/information. In this proposed KGCMLP technique both sender and receiver uses an identical multilayer perceptrons. Both perceptrons are start synchronization by exchanging some control frames. During synchronization process message integrity test an...

Accurate prediction of long-term electricity demand has a significant role in demand side management and electricity network planning and operation. Demand over-estimation results in over-investment in network assets, driving up the electricity prices, while demand underestimation may lead to under-investment resulting in unreliable and insecure electricity. In this manuscript, we apply deep ne...

This paper investigates the use of n-tuple systems as position value functions for the game of Othello. The architecture is described, and then evaluated for use with temporal difference learning. Performance is compared with previously developed weighted piece counters and multi-layer perceptrons. The n-tuple system is able to defeat the best performing of these after just five hundred games o...

This paper presents a model for the probability of correct classification for the Cooperative Modular Neural Network (CMNN). The model enables the estimation of the performance of the CMNN using parameters obtained from the data set. The performance estimates for the experiments presented are quite accurate (less than 1% relative difference). We compare the CMNN with a multilayer perceptron wit...

Neural networks, particularly the multilayer perceptron, have been used extensively in automated signal classification systems with classification accuracy as the figure of merit. Three important issues that can enhance the utility of these systems are (i) incremental learning, (ii) confidence or reliability measures and (iii) performance improvement through continual learning. This paper inves...

This paper presents a fault classification method which makes use of a Takagi-Sugeno neuro-fuzzy model and Pseudomodal energies calculated from the vibration signals of cylindrical shells. The calculation of Pseudomodal Energies, for the purposes of condition monitoring, has previously been found to be an accurate method of extracting features from vibration signals. This calculation is therefo...

An algorithm for segmenting skin regions in color images using color and edge information is presented. Skin colored regions are first detected using a Bayesian model of the human skin color. These regions are further segmented into skin region candidates that satisfy the homogeneity property of the human skin. We show that Bayesian skin color model outperforms many other models such as the pie...

The emission rate of minority atmospheric gases is inferred by a new approach based on neural networks. The new network applied is the multi-layer perceptron with backpropagation algorithm for learning. The identification of these surface fluxes is an inverse problem. A comparison between the new neural-inversion and regularized inverse solutions is performed. The results obtained from the neur...