220 research outputs found
A Study on the Suitability of Genetic Algorithm for Adaptive Channel Equalization
Adaptive algorithms such as Least-Mean-Square (LMS) based channel equalizer aim to minimize the Intersymbol Interference (ISI) present in the transmission channel. However the adaptive algorithms suffer from long training time and undesirable local minima during training mode. These disadvantages of the adaptive algorithms for channel equalization have been discussed in the literature. In this paper, we propose a new adaptive channel equalizer using Genetic Algorithm (GA) which is essentially a derivative free optimization tool. This algorithm is suitably used to update the weights of the equalizer. The performance of the proposed channel equalizer is evaluated in terms of mean square error (MSE) and convergence rate and is compared with its LMS and RLS counter parts. It is observed that the new adaptive equalizer based GA offer improved performance so far as the accuracy of reception is concerned.DOI:http://dx.doi.org/10.11591/ijece.v2i3.31
Low Complexity Adaptive Noise Canceller for Mobile Phones Based Remote Health Monitoring
Mobile phones are gaining acceptance to become an effective tool for remote health monitoring. On one hand, during electrocardiographic (ECG) recording, the presence of various forms of noise is inevitable. On the other hand, algorithms for adaptive noise cancellation must be shared by limited computational power offered by the mobile phones. This paper describes a new adaptive noise canceller scheme, with low computational complexity, for simultaneous cancellation of various forms of noise in ECG signal. The proposed scheme is comprised of two stages. The first stage uses an adaptive notch filters, which are used to eliminate power-line interference from the primary and reference input signals, whereas the other noises are reduced using modified LMS algorithm in the second stage. Low power consumption and lower silicon area are key issues in mobile phones based adaptive noise cancellation. The reduction in complexity is obtained by using log-log LMS algorithm for updating adaptive filters in the proposed scheme. A comprehensive complexity and performance analysis between the proposed and traditional schemes are provided.DOI:http://dx.doi.org/10.11591/ijece.v4i3.553
Comparative Performance Investigations of Stochastic and Genetic Algorithms Under Fast Dynamically Changing Environment in Smart Antennas
In a mobile communication systems, the number of observation data (snapshots) used for covariance matrix estimation can be insufficient, which often occurs due to fast dynamically changing environment or signal characteristics are rapidly changing. In these situations, the performance of the standard adaptive algorithms such as LMS are known to degrade substantially. In this paper, we propose the use of a Genetic Algorithm (GA) to perform the adaptation control of the system parameters under dynamically changing environments The GA-based beamformer has nearly optimal interference cancellation under dynamic conditions, and makes the output SINR consistently close to the optimal one regardless of the number of snapshot used. Other advantages of the GA is its simplicity and fast convergence provided that the parameters are appropriately chosen, which makes it a practical algorithm for beamforming in smart antenna. Simulation results validate substantial performance improvements relative to other standard adaptive algorithms. Although, the use of GA is not new in smart antenna technology, the performance evaluation of the genetic optimization under fast dynamically changing environment has not been investigated to the best of my knowledge and it is of great practical significance.DOI:http://dx.doi.org/10.11591/ijece.v2i1.11
Performance Optimization of the Arbitrary Arrays with Randomly Distributed Elements for Wireless Sensor Networks
Beamforming using regular linear or planar arrays, in which their elements are uniformly spaced is widely studied for various applications. However, in the wireless sensor network applications, such regular arrays are not possible to build. Thus, they are usually built with randomly distributed planar elements. Generating the required beamforming from such randomly distributed arrays that can provide a significant improvement in the wireless sensor network performance is a real challenging issue. In this paper, the amplitude and phase of each random element within the arbitrary bounded area is optimized such that its corresponding array pattern acts as a beam-steerable with minimum sidelobe level and a certain beamwidth. Simulation results under various optimization constraints are given to show the effectiveness of the considered random array. The effect of changing the total number of array elements on the array performance, such as beamwidth, minimum sidelobe level, and the gain were also investigated
Radiation Pattern Synthesis of Planar Arrays Using Parasitic Patches Fed by a Small Number of Active Elements
In this chapter, several planar array designs based on the use of a small number of the active elements located at the center of the planar array surrounded by another number of the uniformly distributed parasitic elements are investigated. The parasitic elements are used to modify the radiation pattern of the central active elements. The overall radiation pattern of the resulting planar array with a small number of active elements is found to be comparable to that of the fully active array elements with a smaller sidelobe level (SLL) at the cost of a relatively wider beamwidth and lower directivity. Nevertheless, the uses of only a small number of the active elements provide a very simple feeding network that reduces the cost and the complexity of the array. Simulation results which have been computed using computer simulation technology-microwave studio (CST-MWS) show that the sidelobe level of the designed array pattern with parasitic elements is considerably better than that of the similar fully active array elements. The proposed array can be effectively and efficiently used in the applications that require wider antenna beams
Sidelobe Nulling by Optimizing Selected Elements in the Linear and Planar Arrays
Currently, there are significant interests in the antenna arrays that are composed of a large number of elements controlled by an appropriate optimizer for the next generation of wireless communication systems, where the massive multiple-inputs multiple-outputs (MIMO) systems are expected to play a major role in such systems. On the other hand, the interfering signals which are expected to rise dramatically in these applications due to the crowded spectrum represent a real challenging issue that limits and causes great degradation in their performances. To achieve an optimum performance, these antenna arrays should be optimized and designed to have maximum gain, narrow beam width, and very low sidelobes or deep nulls. Toward achieving this goal, the overall array performance can be either electronically controlling the design parameters, such as amplitude and/or phase excitations of the individual elements, or mechanically controlling the element positions. This chapter discusses techniques proposed for sidelobe nulling by optimizing the excitations and positions of selected elements in the linear and planar arrays
Women’s Knowledge and Perception of Teratogens and Their Effect in First Trimester of Pregnancy in Antenatal Care Units of Secondary Health Facilities in Kebbi State, Nigeria
The study was conducted to evaluate the knowledge and perception of teratogens among pregnant women attending antenatal care units in secondary health facility in kebbi state. A descriptive survey design using a probability sampling technique was employed and 120 patients were selected using a questionnaire as an instrument for data collection. The data collected was analyzed using descriptive statistics, the results was presented in frequency distribution tables and percentages. On knowledge and perception of the respondents on teratogens effect, Findings shows that about 48.3 % of the respondents were aware of the teratogens; while about 51.7 % were not aware of the teratogens and their effect. On the substances that are teratogens in nature 35 % said are the most common teratogens,34.2 % of the respondents said dust is the common teratogens they know.meanwhile;30.8% of the respondents said alcohol is the dangerous teratogens. It can be noted that majority of the respondents (49.2 %) takes drugs on prescription only. While 24.1% takes their drugs on non-prescription bases. 13.3 % of the respondent do smokes and also 13.3% of the respondents keep appointment with A.N.C visits. Also those respondents that visits hospital for any new complains were 17%, while those respondents that use herbal medicine to treat any ailment were 83%.. In conclusion there is no doubt that menace of teratogens effect among pregnant women is increasingly becoming a major public health problem in our society.it was recommended that all pregnant women especially primis should be cautioned extensively about teratogens substances and their consequent effect. This project has shown that the level of knowledge of teratogenic substances and their effect in first trimester of pregnancy is low in secondary health facility in kebbi state.  KEY WORDS KNOWLEDGE: information or learning gain through experience or education. PERCEPTION: a way of regarding, understanding or interpreting something. TERATOGEN: any substance, agent, or process that induces the formation of developmental abnormalities in a fetus. TRIMESTER: any one of three successive three-month periods into which a pregnancy is divided. EFFECT: a change which is a result or consequence of an action or other cause. PREGNANCY: the condition or period of being pregnant. WOMAN: an adult human female. DOI: 10.7176/JHMN/82-06 Publication date: November 30th 202
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