Preferred Language
Articles
/
joe-113
A Hybrid Coefficient Decimation- Interpolation Based Reconfigurable Low Complexity Filter Bank for Cognitive Radio
...Show More Authors

Non uniform channelization is a crucial task in cognitive radio receivers for obtaining separate channels from the digitized wideband input signal at different intervals of time. The two main requirements in the channelizer are reconfigurability and low complexity. In this paper, a reconfigurable architecture based on a combination of Improved Coefficient Decimation Method (ICDM) and Coefficient Interpolation Method (CIM) is proposed. The proposed Hybrid Coefficient Decimation-Interpolation Method (HCDIM) based filter bank (FB) is able to realize the same number of channels realized using (ICDM) but with a maximum decimation factor divided by the interpolation factor (L), which leads to less deterioration in stop band attenuation (SA). The proposed architecture is able to realize a greater number of sub-bands locations. The proposed (HCDIM) based (FB) shows an inherent low complexity offered by the (CIM) technique when compared with the alternative FBs. The reduction in the number of multiplications is by 50.77% compared with ICDM in non-uniform channelization, while the reduction in the number of multiplications is about 59.64% over the discrete Fourier transform (DFTFB) and 31.19% over ICDM based FB in uniform channelization.

 

 

View Publication Preview PDF
Quick Preview PDF
Publication Date
Thu Jul 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Application
Forecasting enhancement using a hodrick-prescott filter
...Show More Authors

: Sound forecasts are essential elements of planning, especially for dealing with seasonality, sudden changes in demand levels, strikes, large fluctuations in the economy, and price-cutting manoeuvres for competition. Forecasting can help decision maker to manage these problems by identifying which technologies are appropriate for their needs. The proposal forecasting model is utilized to extract the trend and cyclical component individually through developing the Hodrick–Prescott filter technique. Then, the fit models of these two real components are estimated to predict the future behaviour of electricity peak load. Accordingly, the optimal model obtained to fit the periodic component is estimated using spectrum analysis and Fourier mod

... Show More
Preview PDF
Scopus
Publication Date
Wed Mar 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Design a radio receiver for solar activity observation in VLF band
...Show More Authors

Solar activity monitoring is important in our life because of its direct or indirect influence on our life, not only on ionospheric communications. To study solar activity, researchers need measuring and monitoring instruments, these instruments are mostly expensive and are not available in all universities. In this paper, a very low frequency radio receiver had been designed and implemented with components available in most markets to support the researchers, college students, and radio astronomy amateurs with a minimum input voltage less than 100µV, an output voltage less than 135 m V with no distortion and an overall gain of 34dB. A comparison had been done between two circuit structures using a workbench software program and experim

... Show More
View Publication Preview PDF
Scopus (1)
Scopus Crossref
Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Low-Distortion MMSE Estimator for Speech Enhancement Based on Hahn Moments
...Show More Authors

View Publication
Scopus (3)
Crossref (2)
Scopus Crossref
Publication Date
Sun Dec 31 2023
Journal Name
Iraqi Journal Of Information And Communication Technology
EEG Signal Classification Based on Orthogonal Polynomials, Sparse Filter and SVM Classifier
...Show More Authors

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

... Show More
View Publication Preview PDF
Crossref (4)
Crossref
Publication Date
Fri May 01 2026
Journal Name
Statistics, Optimization & Information Computing
Hybrid Modeling of Currency Circulation Volatility: Evidence from the Central Bank of Iraq
...Show More Authors

The currency in circulation is a key element of the monetary supply system of the Iraqi economy because itreflects the level of economic activity and the liquidity level in the market. It can be expressed as an important tool when formulating monetary policy. This research aims to analyze and forecast the behavior of the currency in circulation in Iraq using the ARMA-GARCH model for monthly data from 2004 to 2025 to understand the dynamics of monetary liquidity, The sample was divided into two parts: approximately 80% for the training set (2004-2021), and approximately 20% for the testing set (2022-2025). Data were analyzed in Python using many packages. The results showed that the time series was initially non-stationary but became

... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Hybrid CNN-based Recommendation System
...Show More Authors

Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

... Show More
View Publication Preview PDF
Scopus (9)
Crossref (6)
Scopus Crossref
Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Design and Evaluation of a Polarizer Filter
...Show More Authors

This research includes theoretical and evaluation design of a polarizer filter of high transmission in the near IR region of (900-1200nm) for different incidence angles to obtain a long wave and short wave pass filter using analytical calculations. Results refer to a new configuration design in fewer layers than used in previous studies in the long wave pass at incidence angles (45o,50o,55o). Adopted Hafnium dioxide (HfO2) and Magnesium fluoride (MgF2) as coating material at design wavelength (933nm), the study also included design short wave pass polarizer by using the same coating material.

View Publication Preview PDF
Scopus (3)
Crossref (3)
Scopus Clarivate Crossref
Publication Date
Thu Apr 01 2021
Journal Name
Computer Methods And Programs In Biomedicine
A hybrid approach based on multiple Eigenvalues selection (MES) for the automated grading of a brain tumor using MRI
...Show More Authors

View Publication
Scopus (42)
Crossref (38)
Scopus Clarivate Crossref
Publication Date
Fri Mar 15 2024
Journal Name
2024 International Conference On Distributed Computing And Optimization Techniques (icdcot)
Reconfigurable Microstrip Antenna Design Fifth Generation (5G) System
...Show More Authors

View Publication
Scopus (3)
Scopus Crossref
Publication Date
Sun Feb 24 2019
Journal Name
Iraqi Journal Of Physics
Comparison of three interpolation methods for the average monthly temperature in the south of Iraqi zone
...Show More Authors

This study focuses on evaluating the suitability of three interpolation methods in terms of their accuracy at climate data for some provinces of south of Iraq. Two data sets of maximum and minimum temperature in February 2008 from nine meteorological stations located in the south of Iraq using three interpolation methods. ArcGIS is used to produce the spatially distributed temperature data by using IDW, ordinary kriging, and spline. Four statistical methods are applied to analyze the results obtained from three interpolation methods. These methods are RMSE, RMSE as a percentage of the mean, Model efficiency (E) and Bias, which showed that the ordinary krigingis the best for this data from other methods by the results that have b

... Show More
View Publication Preview PDF
Crossref (1)
Crossref