Abstract: This paper presents a novel fractal antenna structure
proposed for UWB (Ultra – Wideband) applications. The frequency
band 3.1-10.6GHz released by FCC (Federal Communication
Commission) as the commercial operation of UWB has been chosen
as frequency range for this antenna based on coplanar waveguide
(CPW) feed and circular shapes fulfilled according to fractal
geometry. The proposed antenna is validated and designed by using
an FR4 substrate with overall area of 34x43 mm2. The simulated
results performed by CST-Microwave Studio and compared by ADS
(Advanced Design System) show good matching input impedance
with return loss less than -10dB between 2.9 GHz and 11 GHz.
Abstract: This paper proposes evaluation of sound parameterization methods in recognizing some spoken Arabic words, namely digits from zero to nine. Each isolated spoken word is represented by a single template based on a specific recognition feature, and the recognition is based on the Euclidean distance from those templates. The performance analysis of recognition is based on four parameterization features: the Burg Spectrum Analysis, the Walsh Spectrum Analysis, the Thomson Multitaper Spectrum Analysis and the Mel Frequency Cepstral Coefficients (MFCC) features. The main aim of this paper was to compare, analyze, and discuss the outcomes of spoken Arabic digits recognition systems based on the selected recognition features. The results acqired confirm that the use of MFCC features is a very promising method in recognizing Spoken Arabic digits.
Abstract: ICA which is generally used for blind source separation
problem has been tested for feature extraction in Speech recognition
system to replace the phoneme based approach of MFCC. Applying
the Cepstral coefficients generated to ICA as preprocessing has
developed a new signal processing approach. This gives much better
results against MFCC and ICA separately, both for word and speaker
recognition. The mixing matrix A is different before and after MFCC
as expected. As Mel is a nonlinear scale. However, cepstrals
generated from Linear Predictive Coefficient being independent
prove to be the right candidate for ICA. Matlab is the tool used for
all comparisons. The database used is samples of ISOLET.