We present a speech driven real-time viseme recognition system based on Artificial Neural Network (ANN). A Multi-Layer Perceptron (MLP) is used to provide a light and responsive framework, adapted to the final application (i.e., the animation of the lips of an avatar on multi-task platforms with embedded resources and latency constraints). Several improvements of this system are studied such as...

This paper presents the results of modelling to predict the effluent biological oxygen demand (BOD5) concentration for primary clarifiers using a hybridisation of unsupervised and supervised artificial neural networks. The hybrid model is based on the unsupervised self-organising map (SOM) whose features were then used to train a multi-layered perceptron, feedforward back propagation artificial...

One of the most severe threats to revenue and quality of service in telecom providers is fraud. The advent of new technologies has provided fraudsters new techniques to commit fraud. SIM box fraud is one of such fraud that has emerged with the use of VOIP technologies. In this work, a total of nine features found to be useful in identifying SIM box fraud subscriber are derived from the attribut...

Abstract—A glia is a nervous cell in the brain. Currently, the glia is known as a important cell for the human’s cerebration. Because the glia transmits signals to neurons and other glias. We notice features of the glia and consider to apply it for an artificial neural network. In this paper, we propose a Multi-layer perceptron (MLP) with pulse glial chain. The pulse glial chain is inspired fro...

There are a lot of extensions made to the classic model of multi-layer perceptron (MLP). A notable amount of them has been designed to hasten the learning process without considering the quality of generalization. The paper proposes a new MLP extension based on exploiting topology of the input layer of the network. Experimental results show the extended model to improve upon generalization capa...

objective(s): a fast and reliable evaluation of the binding energy from a single conformation of a molecular complex is an important practical task. artificial neural networks (anns) are strong tools for predicting nonlinear functions which are used in this paper to predict binding energy. we proposed a structure that obtains binding energy using physicochemical molecular descriptions of the se...

Chaotic systems are sensitive to initial conditions, system parameters and topological transitivity and these properties are also remarkable for cryptanalysts. Noise like behavior of chaotic systems is the main reason of using these systems in cryptology. However some properties of chaotic systems such as synchronization, fewness of parameters etc. cause serious problems for cryptology. In this...

you may have heard that the Brain is plastic. As you know the brain is not made of plastic, Brain Plasticity also called Neuroplasticity. Brain plasticity is a physical process. Gray matter can actually shrink or thicken neural connections can be forged and refined or weakened and severed. Brain Plasticity refers to the brain’s ability to change throughout life. The brain has the amazing abilit...