Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Multiwavelet


Arabic Word Recognition Based on 3D Radon and Multiwavelet Neural Network

Tarik Zeyad Ismaeel

Engineering and Technology Journal, 2013, Volume 31, Issue 7, Pages 1418-1430

In this paper, an automatic speaker–independent Arabic word speech recognition system is presented using 3D Radon and Multiwavelet neural network. The approach contains combining multiwavelet theory to neural network which lead to fabricate a Multiwavenet. Position and dilation of the Multiwavenets are fixed and the weights are optimized according to learning algorithm in the network. The feature extraction for real Arabic word signals through 3D radon model is used. The proposed terminology here is training process for some words of all speakers done in Multiwavenet learning phase then test for the other sample speech signals for speakers have been used in Multiwavenet classification phase. Success theory of Multiwavenets has been generalized by extension to biorthogonal wavelets which lead to identification system development. Results show the effectiveness of the proposed system presented in this paper. The accuracy in the detection process was 86% when using utterances outside the training database and around 94% when using the whole utterances database in system test process. The proposed algorithms were implemented using MATLAB2011a.

Wavelet & Multiwavelet Lost Block Reconstruction in Noisey Environment

Atheer A. Sabri; Mutaz S. Abdul-Wahab; Waleed A. Mahmoud

Engineering and Technology Journal, 2009, Volume 27, Issue 4, Pages 717-726

In this paper, an algorithm for reconstruction of a completely lost blocks
using the discrete wavelet and multiwavelet transforms are tested under noisey
environment.
The algorithms examined in this paper do not require a DC estimation method.
While most of the previuosly reconstruction methods assume that the DC value is
available or a DC estimation is required.
The reconstruction is achieved using the Boundary Interpolation (BI) which is
based on wavelet transform. The algorithm’s performance is further improved
through the modification of the Boundary Interpolation algorithm.
Another algorithm is studied in this paper which is based on the multiwavelet
transform.
The effect of adding a Gaussian noise to the image on the performance of
reconstruction of the algorithms mentioned in this paper is studied.