Nouma Izeboudjen

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The aim of this paper is to propose a new classification approach of artificial neural networks hardware. Our motivation behind this work is justified by the following two arguments: first, during the last two decades a lot of approaches have been proposed for classification of neural networks hardware. However, at present there is not a clear consensus on(More)
The aim of this paper is to propose a new high-level hardware design reuse methodology for automatic generation of artificial neural networks (ANNs) descriptions. A case study of the back propagation (BP) algorithm is proposed. To achieve our goal, the proposed design methodology is based on a modular design of the ANN. The originality of the work is the(More)
INTRODUCTION Artificial neural networks (ANNs) are systems which are derived from the field of neuroscience and are characterized by intensive arithmetic operations. These net-(1943), there has been much discussion on the topic of ANNs implementation, and a huge diversity of ANNs has been designed (C. Lindsey & T. Lindblad, 1994). The benefits of using such(More)
The aim of this paper is to present a new System on Chip (SoC) reconfigurable gateway architecture for Voice over Internet Telephony (VOIP). Our motivation behind this work is justified by the following arguments: most of VOIP solutions proposed in the market are based on the use of a general purpose processor and a DSP circuit. In these solutions, the use(More)
ASIC (Application Specific Integrated Circuit) design verification takes as long as the designers take to describe synthesis and implement the design. A hybrid approach, where the design is first prototyped on an FPGA (Field-programmable gate array) platform for functional validation and then implemented as an ASIC allows earlier defect detection in the(More)
Embedded system intends to realize portable systems, while reducing chip connect, device size and power dissipation. These systems have obtained great tallness due to their ample fields of application and, it's lower costs compared with the traditional computer systems. The target of this paper is to show how to design and implement an embedded system based(More)
The electrocardiogram (ECG) is an important tool for providing information about functional status of the heart. Analysis of ECG is of great importance in the detection of cardiac anomalies. This paper presents a diagnostic system for cardiac arrhythmias from ECG data, using an artificial neural network classifier. In this article we propose a new method(More)