A Novel A2-based Neural Network Model for Voice Prediction

Abstract

A novel “Multi-Layer Perceptron” (MLP) model, based on the new A2 arithmetic is investigated in this paper. The already implemented A2 arithmetic operators, such as addition and multiplication are used to predict voice signals. One of the main techniques related to this field is the neuronal training. Unlike the static networks, where the training is done in a software manner before being prototyped, we focus ourselves on the realization of a dynamic neuronal system where the training is done continuously within the circuit. The chosen network topology will be justified later in the following paragraph. Also, the elaborated network architecture as well as a comparative study of the obtained performances compared to previous works will be the subject of the following paragraphs.

Authors and Affiliations

Hatem Boukadida| University of Sousse Higher Institute of Applied Science and Technology Sousse, Tunisia, Hassen El Fayedh| University of Sousse Higher Institute of Applied Science and Technology Sousse, Tunisia, Zied Gafsi| University of Monastir Faculty of Science of Monastir Monastir, Tunisia, Kamel Besbes| University of Monastir Faculty of Science of Monastir Monastir, Tunisia

Keywords

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  • EP ID EP8439
  • DOI -
  • Views 318
  • Downloads 22

How To Cite

Hatem Boukadida, Hassen El Fayedh, Zied Gafsi, Kamel Besbes (2015). A Novel A2-based Neural Network Model for Voice Prediction. International Journal of Electronics Communication and Computer Technology, 5(3), 848-853. https://europub.co.uk/articles/-A-8439