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All Journal International Journal of Reconfigurable and Embedded Systems (IJRES) Indonesian Journal of Electrical Engineering and Computer Science
Abdelhalim Zekry
Ain shams University
Economics, Econometrics & Finance

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FPGA implementation of Lempel-Ziv data compression Gody Mostafa; Abdelhalim Zekry; Hatem Zakaria
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 10, No 2: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v10.i2.pp99-108

Abstract

When transmitting the data in digital communication, it is well desired that the transmitting data bits should be as minimal as possible, so many techniques are used to compress the data. In this paper, a Lempel-Ziv algorithm for data compression was implemented through VHDL coding. One of the most lossless data compression algorithms commonly used is Lempel-Ziv. The work in this paper is devoted to improve the compression rate, space-saving, and utilization of the Lempel-Ziv algorithm using a systolic array approach. The developed design is validated with VHDL simulations using Xilinx ISE 14.5 and synthesized on Virtex-6 FPGA chip. The results show that our design is efficient in providing high compression rates and space-saving percentage as well as improved utilization. The Throughput is increased by 50% and the design area is decreased by more than 23% with a high compression ratio compared to comparable previous designs.
Sparse Modeling with Applications to Speech Processing: A Survey Ahmed Omara; Alaa Hefnawy; Abdelhalim Zekry
Indonesian Journal of Electrical Engineering and Computer Science Vol 2, No 1: April 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v2.i1.pp161-167

Abstract

Nowadays, there has been a growing interest in the study of sparse approximation of signals. Using an over-complete dictionary consisting of prototype signals or atoms, signals are described by sparse linear combinations of these atoms. Applications that use sparse representation are many and include compression, source separation, enhancement, and regularization in inverse problems, feature extraction, and more. This article introduces a literature review of sparse coding applications in the field of speech processing.
Co-Authors Ahmed Omara Alaa Hefnawy Gody Mostafa Hatem Zakaria