The Experts below are selected from a list of 15144 Experts worldwide ranked by ideXlab platform
Albrecht E. Melchinger - One of the best experts on this subject based on the ideXlab platform.
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Best linear unbiased prediction and Optimum Allocation of test resources in maize breeding with doubled haploids
Theoretical and Applied Genetics, 2011Co-Authors: Xuefei Mi, Thilo Wegenast, Baldev S. Dhillon, Albrecht E. MelchingerAbstract:With best linear unbiased prediction (BLUP), information from genetically related candidates is combined to obtain more precise estimates of genotypic values of test candidates and thereby increase progress from selection. We developed and applied theory and Monte Carlo simulations implementing BLUP in 2 two-stage maize breeding schemes and various selection strategies. Our objectives were to (1) derive analytical solutions of the mixed model equations under two breeding schemes, (2) determine the Optimum Allocation of test resources with BLUP under different assumptions regarding the variance component ratios for grain yield in maize, (3) compare the progress from selection using BLUP and conventional phenotypic selection based on mean performance solely of the candidates, and (4) analyze the potential of BLUP for further improving the progress from selection. The breeding schemes involved selection for testcross performance either of DH lines at both stages (DHTC) or of S_1 families at the first stage and DH lines at the second stage (S_1TC-DHTC). Our analytical solutions allowed much faster calculations of the Optimum Allocations and superseded matrix inversions to solve the mixed model equations. Compared to conventional phenotypic selection, the progress from selection was slightly higher with BLUP for both optimization criteria, namely the selection gain and the probability to select the best genotypes. The Optimum Allocation of test resources in S_1TC-DHTC involved ≥10 test locations at both stages, a low number of crosses (≤6) each with 100–300 S_1 families at the first stage, and 500–1,000 DH lines at the second stage. In breeding scheme DHTC, the Optimum number of test candidates at the first stage was 5–10 times larger, whereas the number of test locations at the first stage and the number of test candidates at the second stage were strongly reduced compared to S_1TC-DHTC.
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Optimum Allocation of resources for qtl detection using a nested association mapping strategy in maize
Theoretical and Applied Genetics, 2010Co-Authors: Benjamin Stich, Hans Peter Maurer, H F Utz, Hanspeter Piepho, Albrecht E. MelchingerAbstract:In quantitative trait locus (QTL) mapping studies, it is mandatory that the available financial resources are spent in such a way that the power for detection of QTL is maximized. The objective of this study was to optimize for three different fixed budgets the power of QTL detection 1 - b* in recombinant inbred line (RIL) populations derived from a nested design by varying (1) the genetic complexity of the trait, (2) the costs for developing, genotyping, and phenotyping RILs, (3) the total number of RILs, and (4) the number of environments and replications per environment used for phenotyping. Our computer simulations were based on empirical data of 653 single nucleotide polymorphism markers of 26 diverse maize inbred lines which were selected on the basis of 100 simple sequence repeat markers out of a worldwide sample of 260 maize inbreds to capture the maximum genetic diversity. For the standard scenario of costs, the Optimum number of test environments (Eopt) ranged across the examined total budgets from 7 to 19 in the scenarios with 25 QTL. In comparison, the Eopt values observed for the scenarios with 50 and 100 QTL were slightly higher. Our finding of differences in 1 - b* estimates between experiments with optimally and sub-optimally allocated resources illustrated the potential to improve the power for QTL detection without increasing the total resources necessary for a QTL mapping experiment. Furthermore, the results of our study indicated that also in studies using the latest genomics tools to dissect quantitative traits, it is required to evaluate the individuals of the mapping population in a high number of environments with a high number of replications per environment.
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hybrid maize breeding with doubled haploids iv number versus size of crosses and importance of parental selection in two stage selection for testcross performance
Theoretical and Applied Genetics, 2008Co-Authors: Thilo Wegenast, Albrecht E. Melchinger, Friedrich H Utz, Friedrich C H Longin, Hans Peter Maurer, Jochen C ReifAbstract:Parental selection influences the gain from selection and the Optimum Allocation of test resources in breeding programs. We compared two hybrid maize (Zea mays L.) breeding schemes with evaluation of testcross progenies: (a) doubled haploid (DH) lines in both stages (DHTC) and (b) S1 families in the first stage and DH lines within S1 families in the second stage (S1TC-DHTC). Our objectives were to (1) determine the Optimum Allocation regarding the number of crosses, S1 families, DH lines, and test locations, (2) investigate the impact of parental selection on the Optimum Allocation and selection gain (ΔG), and (3) compare the maximum ΔG achievable with each breeding scheme. Selection gain was calculated by numerical integration. Different assumptions were made regarding the budget, variance components, correlation between the mean phenotypic performance of the parents and the mean genotypic value of the testcross performance of their progenies (ρP), and the composition of the finally selected test candidates. In comparison with randomly chosen crosses, maximum ΔG was largely increased with parental selection in both breeding schemes. With an increasing correlation ρP, this superiority increased strongly, while the Optimum number of crosses decreased in favor of an increased number of test candidates within crosses. Thus, concentration on few crosses among the best parental lines might be a promising approach for short-term success in advanced cycle breeding. Breeding scheme S1TC-DHTC led to a larger ΔG but had a longer cycle length than DHTC. However, with further improvements in the DH technique and the realization of more than two generations per year, early testing of S1 families prior to production of DH lines would become very attractive in hybrid maize breeding.
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hybrid maize breeding with doubled haploids iii efficiency of early testing prior to doubled haploid production in two stage selection for testcross performance
Theoretical and Applied Genetics, 2007Co-Authors: Friedrich C H Longin, Jochen C Reif, Friedrich H Utz, Wolfgang Schipprack, Thilo Wegenast, Albrecht E. MelchingerAbstract:Early testing prior to doubled haploid (DH) production is a promising approach in hybrid maize breeding. We (1) determined the Optimum Allocation of the number of S1 families, DH lines, and test locations for two different breeding schemes, (2) compared the maximum selection gain achievable under both breeding schemes, and (3) investigated limitations in the current method of DH production. Selection gain was calculated by numerical integration in two-stage breeding schemes with evaluation of testcross progenies of (1) DH lines in both stages (DHTC), or (2) S1 families in the first and DH lines within S1 families in the second stage (S1TC-DHTC). Different assumptions were made regarding the budget, variance components, and time of DH production within S1 families. Maximum selection gain in S1TC-DHTC was about 10% larger than in DHTC, indicating the large potential of early testing prior to DH production. The Optimum Allocation of test resources in S1TC-DHTC involved similar numbers of test locations and test candidates in both stages resulting in a large Optimum number of S1 families in the first stage and DH lines within the best two S1 families in the second stage. The longer cycle length of S1TC-DHTC can be compensated by haploid induction of individual S1 plants instead of S1 families. However, this reduces selection gain largely due to the current limitations in the DH technique. Substantial increases in haploid induction and chromosome doubling rates as well as reduction in costs of DH production would allow early testing of S1 lines and subsequent production and testing of DH lines in a breeding scheme that combines high selection gain with a short cycle length.
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Hybrid maize breeding with doubled haploids: II. Optimum type and number of testers in two-stage selection for general combining ability
Theoretical and Applied Genetics, 2007Co-Authors: C F H Longin, Albrecht E. Melchinger, H F Utz, Jochen C ReifAbstract:Optimum Allocation of test resources is of crucial importance for the efficiency of breeding programs. Our objectives were to (1) determine the Optimum Allocation of the number of lines, test locations, as well as number and type of testers in hybrid maize breeding using doubled haploids with two breeding strategies for improvement of general combining ability (GCA), (2) compare the maximum selection gain (Δ G ) achievable under both strategies, and (3) give recommendations for the Optimum implementation of doubled haploids in commercial hybrid maize breeding. We calculated Δ G by numerical integration for two two-stage selection strategies with evaluation of (1) testcross performance in both stages (BS1) or (2) line per se performance in the first stage followed by testcross performance in the second stage (BS2). Different assumptions were made regarding the budget, variance components (VCs), and the correlation between line per se performance and GCA. Selection gain for GCA increased with a broader genetic base of the tester. Hence, testers combining a large number of divergent lines are advantageous. However, in applied breeding programs, the use of single- or double-cross testers in the first and inbred testers in the second selection stage may be a good compromise between theoretical and practical requirements. With a correlation between line per se performance and GCA of 0.50, Δ G for BS1 is about 5% higher than for BS2, if an economic weight of line per se performance is neglected. With increasing economic weight of line per se performance, relative efficiency of BS2 increased rapidly resulting in a superiority of BS2 over BS1 already for an economic weight for line per se performance larger than 0.1. Considering the importance of an economic seed production, an economic weight larger than 0.1 seems realistic indicating the necessity of separate breeding strategies for seed and pollen parent heterotic groups.
Jochen C Reif - One of the best experts on this subject based on the ideXlab platform.
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hybrid maize breeding with doubled haploids iv number versus size of crosses and importance of parental selection in two stage selection for testcross performance
Theoretical and Applied Genetics, 2008Co-Authors: Thilo Wegenast, Albrecht E. Melchinger, Friedrich H Utz, Friedrich C H Longin, Hans Peter Maurer, Jochen C ReifAbstract:Parental selection influences the gain from selection and the Optimum Allocation of test resources in breeding programs. We compared two hybrid maize (Zea mays L.) breeding schemes with evaluation of testcross progenies: (a) doubled haploid (DH) lines in both stages (DHTC) and (b) S1 families in the first stage and DH lines within S1 families in the second stage (S1TC-DHTC). Our objectives were to (1) determine the Optimum Allocation regarding the number of crosses, S1 families, DH lines, and test locations, (2) investigate the impact of parental selection on the Optimum Allocation and selection gain (ΔG), and (3) compare the maximum ΔG achievable with each breeding scheme. Selection gain was calculated by numerical integration. Different assumptions were made regarding the budget, variance components, correlation between the mean phenotypic performance of the parents and the mean genotypic value of the testcross performance of their progenies (ρP), and the composition of the finally selected test candidates. In comparison with randomly chosen crosses, maximum ΔG was largely increased with parental selection in both breeding schemes. With an increasing correlation ρP, this superiority increased strongly, while the Optimum number of crosses decreased in favor of an increased number of test candidates within crosses. Thus, concentration on few crosses among the best parental lines might be a promising approach for short-term success in advanced cycle breeding. Breeding scheme S1TC-DHTC led to a larger ΔG but had a longer cycle length than DHTC. However, with further improvements in the DH technique and the realization of more than two generations per year, early testing of S1 families prior to production of DH lines would become very attractive in hybrid maize breeding.
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hybrid maize breeding with doubled haploids iii efficiency of early testing prior to doubled haploid production in two stage selection for testcross performance
Theoretical and Applied Genetics, 2007Co-Authors: Friedrich C H Longin, Jochen C Reif, Friedrich H Utz, Wolfgang Schipprack, Thilo Wegenast, Albrecht E. MelchingerAbstract:Early testing prior to doubled haploid (DH) production is a promising approach in hybrid maize breeding. We (1) determined the Optimum Allocation of the number of S1 families, DH lines, and test locations for two different breeding schemes, (2) compared the maximum selection gain achievable under both breeding schemes, and (3) investigated limitations in the current method of DH production. Selection gain was calculated by numerical integration in two-stage breeding schemes with evaluation of testcross progenies of (1) DH lines in both stages (DHTC), or (2) S1 families in the first and DH lines within S1 families in the second stage (S1TC-DHTC). Different assumptions were made regarding the budget, variance components, and time of DH production within S1 families. Maximum selection gain in S1TC-DHTC was about 10% larger than in DHTC, indicating the large potential of early testing prior to DH production. The Optimum Allocation of test resources in S1TC-DHTC involved similar numbers of test locations and test candidates in both stages resulting in a large Optimum number of S1 families in the first stage and DH lines within the best two S1 families in the second stage. The longer cycle length of S1TC-DHTC can be compensated by haploid induction of individual S1 plants instead of S1 families. However, this reduces selection gain largely due to the current limitations in the DH technique. Substantial increases in haploid induction and chromosome doubling rates as well as reduction in costs of DH production would allow early testing of S1 lines and subsequent production and testing of DH lines in a breeding scheme that combines high selection gain with a short cycle length.
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Hybrid maize breeding with doubled haploids: II. Optimum type and number of testers in two-stage selection for general combining ability
Theoretical and Applied Genetics, 2007Co-Authors: C F H Longin, Albrecht E. Melchinger, H F Utz, Jochen C ReifAbstract:Optimum Allocation of test resources is of crucial importance for the efficiency of breeding programs. Our objectives were to (1) determine the Optimum Allocation of the number of lines, test locations, as well as number and type of testers in hybrid maize breeding using doubled haploids with two breeding strategies for improvement of general combining ability (GCA), (2) compare the maximum selection gain (Δ G ) achievable under both strategies, and (3) give recommendations for the Optimum implementation of doubled haploids in commercial hybrid maize breeding. We calculated Δ G by numerical integration for two two-stage selection strategies with evaluation of (1) testcross performance in both stages (BS1) or (2) line per se performance in the first stage followed by testcross performance in the second stage (BS2). Different assumptions were made regarding the budget, variance components (VCs), and the correlation between line per se performance and GCA. Selection gain for GCA increased with a broader genetic base of the tester. Hence, testers combining a large number of divergent lines are advantageous. However, in applied breeding programs, the use of single- or double-cross testers in the first and inbred testers in the second selection stage may be a good compromise between theoretical and practical requirements. With a correlation between line per se performance and GCA of 0.50, Δ G for BS1 is about 5% higher than for BS2, if an economic weight of line per se performance is neglected. With increasing economic weight of line per se performance, relative efficiency of BS2 increased rapidly resulting in a superiority of BS2 over BS1 already for an economic weight for line per se performance larger than 0.1. Considering the importance of an economic seed production, an economic weight larger than 0.1 seems realistic indicating the necessity of separate breeding strategies for seed and pollen parent heterotic groups.
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hybrid maize breeding with doubled haploids comparison between selection criteria
Acta Agronomica Hungarica, 2006Co-Authors: C F H Longin, Albrecht E. Melchinger, H F Utz, Jochen C ReifAbstract:The Optimum Allocation of breeding resources is crucial for the efficiency of breeding programmes. The objectives were to (i) compare selection gain ΔGk for finite and infinite sample sizes, (ii) compare ΔGk and the probability of identifying superior hybrids (Pk), and (iii) determine the Optimum Allocation of the number of hybrids and test locations in hybrid maize breeding using doubled haploids. Infinite compared to finite sample sizes led to almost identical Optimum Allocation of test resources, but to an inflation of ΔGk. This inflation decreased as the budget and the number of finally selected hybrids increased. A reasonable Pk was reached for hybrids belonging to the q = 1% best of the population. The Optimum Allocations for Pk(q) and ΔGkwere similar, indicating that Pk(q) is promising for optimizing breeding programmes.
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hybrid maize breeding with doubled haploids i one stage versus two stage selection for testcross performance
Theoretical and Applied Genetics, 2006Co-Authors: Friedrich C H Longin, Friedrich H Utz, Jochen C Reif, Wolfgang Schipprack, Albrecht E. MelchingerAbstract:Optimum Allocation of resources is of fundamental importance for the efficiency of breeding programs. The objectives of our study were to (1) determine the Optimum Allocation for the number of lines and test locations in hybrid maize breeding with doubled haploids (DHs) regarding two optimization criteria, the selection gain ΔGk and the probability Pk of identifying superior genotypes, (2) compare both optimization criteria including their standard deviations (SDs), and (3) investigate the influence of production costs of DHs on the Optimum Allocation. For different budgets, number of finally selected lines, ratios of variance components, and production costs of DHs, the Optimum Allocation of test resources under one- and two-stage selection for testcross performance with a given tester was determined by using Monte Carlo simulations. In one-stage selection, lines are tested in field trials in a single year. In two-stage selection, Optimum Allocation of resources involves evaluation of (1) a large number of lines in a small number of test locations in the first year and (2) a small number of the selected superior lines in a large number of test locations in the second year, thereby maximizing both optimization criteria. Furthermore, to have a realistic chance of identifying a superior genotype, the probability Pk of identifying superior genotypes should be greater than 75%. For budgets between 200 and 5,000 field plot equivalents, Pk > 75% was reached only for genotypes belonging to the best 5% of the population. As the Optimum Allocation for Pk(5%) was similar to that for ΔGk, the choice of the optimization criterion was not crucial. The production costs of DHs had only a minor effect on the Optimum number of locations and on values of the optimization criteria.
Friedrich C H Longin - One of the best experts on this subject based on the ideXlab platform.
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genomic selection in wheat Optimum Allocation of test resources and comparison of breeding strategies for line and hybrid breeding
Theoretical and Applied Genetics, 2015Co-Authors: Friedrich C H Longin, Tobias WurschumAbstract:The implementation of genomic selection in breeding programs can be recommended for hybrid and line breeding in wheat. High prediction accuracies from genomic selection (GS) were reported for grain yield in wheat asking for the elaboration of efficient breeding strategies applying GS. Our objectives were therefore, (1) to optimize the number of lines, locations and testers in different multi-stage breeding strategies with and without GS, (2) to elaborate the most efficient breeding strategy based on the selection gain and its standard deviation, and (3) to investigate the potential of GS to improve the relative efficiency of hybrid versus line breeding in wheat. We used the open source software package “selectiongain” to optimize the Allocation of resources in different breeding strategies by predicting the expected selection gain for a fixed budget. Classical two-stage phenotypic selection was compared with three GS breeding strategies for line and hybrid breeding in wheat. The ranking of the alternative breeding strategies varied largely in dependence of the GS prediction accuracy. Fast-track breeding strategies based solely on GS were only advantageous for high GS prediction accuracies that is >0.50 and >0.65 for hybrid and line breeding, respectively. However, a GS prediction accuracy across breeding cycles of 0.3 or even less must be assumed as realistic for grain yield in wheat. For this low GS prediction accuracy, the use of GS is advantageous for line but especially for hybrid breeding in wheat. Furthermore, the use of GS in hybrid wheat breeding increased the relative efficiency of hybrid versus line breeding and, thus, might be an important pillar for the establishment of hybrid wheat.
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hybrid maize breeding with doubled haploids iv number versus size of crosses and importance of parental selection in two stage selection for testcross performance
Theoretical and Applied Genetics, 2008Co-Authors: Thilo Wegenast, Albrecht E. Melchinger, Friedrich H Utz, Friedrich C H Longin, Hans Peter Maurer, Jochen C ReifAbstract:Parental selection influences the gain from selection and the Optimum Allocation of test resources in breeding programs. We compared two hybrid maize (Zea mays L.) breeding schemes with evaluation of testcross progenies: (a) doubled haploid (DH) lines in both stages (DHTC) and (b) S1 families in the first stage and DH lines within S1 families in the second stage (S1TC-DHTC). Our objectives were to (1) determine the Optimum Allocation regarding the number of crosses, S1 families, DH lines, and test locations, (2) investigate the impact of parental selection on the Optimum Allocation and selection gain (ΔG), and (3) compare the maximum ΔG achievable with each breeding scheme. Selection gain was calculated by numerical integration. Different assumptions were made regarding the budget, variance components, correlation between the mean phenotypic performance of the parents and the mean genotypic value of the testcross performance of their progenies (ρP), and the composition of the finally selected test candidates. In comparison with randomly chosen crosses, maximum ΔG was largely increased with parental selection in both breeding schemes. With an increasing correlation ρP, this superiority increased strongly, while the Optimum number of crosses decreased in favor of an increased number of test candidates within crosses. Thus, concentration on few crosses among the best parental lines might be a promising approach for short-term success in advanced cycle breeding. Breeding scheme S1TC-DHTC led to a larger ΔG but had a longer cycle length than DHTC. However, with further improvements in the DH technique and the realization of more than two generations per year, early testing of S1 families prior to production of DH lines would become very attractive in hybrid maize breeding.
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hybrid maize breeding with doubled haploids iii efficiency of early testing prior to doubled haploid production in two stage selection for testcross performance
Theoretical and Applied Genetics, 2007Co-Authors: Friedrich C H Longin, Jochen C Reif, Friedrich H Utz, Wolfgang Schipprack, Thilo Wegenast, Albrecht E. MelchingerAbstract:Early testing prior to doubled haploid (DH) production is a promising approach in hybrid maize breeding. We (1) determined the Optimum Allocation of the number of S1 families, DH lines, and test locations for two different breeding schemes, (2) compared the maximum selection gain achievable under both breeding schemes, and (3) investigated limitations in the current method of DH production. Selection gain was calculated by numerical integration in two-stage breeding schemes with evaluation of testcross progenies of (1) DH lines in both stages (DHTC), or (2) S1 families in the first and DH lines within S1 families in the second stage (S1TC-DHTC). Different assumptions were made regarding the budget, variance components, and time of DH production within S1 families. Maximum selection gain in S1TC-DHTC was about 10% larger than in DHTC, indicating the large potential of early testing prior to DH production. The Optimum Allocation of test resources in S1TC-DHTC involved similar numbers of test locations and test candidates in both stages resulting in a large Optimum number of S1 families in the first stage and DH lines within the best two S1 families in the second stage. The longer cycle length of S1TC-DHTC can be compensated by haploid induction of individual S1 plants instead of S1 families. However, this reduces selection gain largely due to the current limitations in the DH technique. Substantial increases in haploid induction and chromosome doubling rates as well as reduction in costs of DH production would allow early testing of S1 lines and subsequent production and testing of DH lines in a breeding scheme that combines high selection gain with a short cycle length.
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hybrid maize breeding with doubled haploids i one stage versus two stage selection for testcross performance
Theoretical and Applied Genetics, 2006Co-Authors: Friedrich C H Longin, Friedrich H Utz, Jochen C Reif, Wolfgang Schipprack, Albrecht E. MelchingerAbstract:Optimum Allocation of resources is of fundamental importance for the efficiency of breeding programs. The objectives of our study were to (1) determine the Optimum Allocation for the number of lines and test locations in hybrid maize breeding with doubled haploids (DHs) regarding two optimization criteria, the selection gain ΔGk and the probability Pk of identifying superior genotypes, (2) compare both optimization criteria including their standard deviations (SDs), and (3) investigate the influence of production costs of DHs on the Optimum Allocation. For different budgets, number of finally selected lines, ratios of variance components, and production costs of DHs, the Optimum Allocation of test resources under one- and two-stage selection for testcross performance with a given tester was determined by using Monte Carlo simulations. In one-stage selection, lines are tested in field trials in a single year. In two-stage selection, Optimum Allocation of resources involves evaluation of (1) a large number of lines in a small number of test locations in the first year and (2) a small number of the selected superior lines in a large number of test locations in the second year, thereby maximizing both optimization criteria. Furthermore, to have a realistic chance of identifying a superior genotype, the probability Pk of identifying superior genotypes should be greater than 75%. For budgets between 200 and 5,000 field plot equivalents, Pk > 75% was reached only for genotypes belonging to the best 5% of the population. As the Optimum Allocation for Pk(5%) was similar to that for ΔGk, the choice of the optimization criterion was not crucial. The production costs of DHs had only a minor effect on the Optimum number of locations and on values of the optimization criteria.
T.a. Gulliver - One of the best experts on this subject based on the ideXlab platform.
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dynamic spectrum management for wcdma dvb heterogeneous systems
IEEE Transactions on Wireless Communications, 2011Co-Authors: Zhiyong Feng, T.a. GulliverAbstract:This paper proposes a novel Dynamic Spectrum Management (DSM) scheme for Wideband Code Division Multiple Access (WCDMA) / Digital Video Broadcasting (DVB) heterogeneous systems. Capacity estimation algorithms for both WCDMA and DVB are developed which consider both the user distribution and characteristics of the hybrid services. Based on these algorithms, a new dynamic spectrum Allocation scheme is presented which allows for Optimum Allocation of resources and maximum secondary spectrum usage. Coloring theory is used to significantly reduce DSM complexity while providing near-optimal performance. Numerical results are given which show that the proposed DSM scheme has better performance than Fixed Spectrum Management (FSM).
Siuly Siuly - One of the best experts on this subject based on the ideXlab platform.
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epileptic eeg signal classification using Optimum Allocation based power spectral density estimation
Iet Signal Processing, 2018Co-Authors: Hadi Ratham Al Ghayab, Siuly Siuly, Shahab AbdullaAbstract:This study proposes a novel approach blending Optimum Allocation (OA) technique and spectral density estimation to analyse and classify epileptic electroencephalogram (EEG) signals. This study employs the OA to determine representative sample points from the original EEG data and then applies periodogram (PD), autoregressive (AR), and the mixture of PD and AR to extract the discriminative features from each OA sample group. The obtained feature sets are evaluated by three popular machine learning methods: support vector machine (SVM), quadratic discriminant analysis (QDA), and k -nearest neighbour (k-NN). Several output coding approaches of the SVM classifier are tested for selecting the best feature sets. This scheme was implemented on a benchmark epileptic EEG database for evaluation and also compared with existing methods. The experimental results show that the OA_AR feature set yields better performances by the SVM with an overall accuracy of 100%, and outperforms the state-of-the-art works with a 14.1% improvement. Thus, the findings of this study prove that the proposed OA-based AR scheme has significant potential to extract features from EEG signals. The proposed method will assist experts to automatically analyse a large volume of EEG data and benefit epilepsy research.
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an Optimum Allocation sampling based feature extraction scheme for distinguishing seizure and seizure free eeg signals
Health Information Science, 2017Co-Authors: Sachin Taran, Varun Bajaj, Siuly SiulyAbstract:Epileptic seizure is the common neurological disorder, which is generally identified by electroencephalogram (EEG) signals. In this paper, a new feature extraction methodology based on Optimum Allocation sampling (OAS) and Teager energy operator (TEO) is proposed for detection of seizure EEG signals. The OAS scheme selects the finite length homogeneous sequence from non-homogeneous recorded EEG signal. The trend of selected sequence by OAS is still non-linear, which is analyzed by non-linear operator TEO. The TEO convert non-linear but homogenous EEG sequence into amplitude–frequency modulated (AM–FM) components. The statistical measures of AM–FM components used as input features to least squares support vector machine classifier for classification of seizure and seizure-free EEG signals. The proposed methodology is evaluated on a benchmark epileptic seizure EEG database. The experimental results demonstrate that the proposed scheme has capability to effectively distinguish seizure and seizure-free EEG signals.
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designing a robust feature extraction method based on Optimum Allocation and principal component analysis for epileptic eeg signal classification
Computer Methods and Programs in Biomedicine, 2015Co-Authors: Siuly Siuly, Yan LiAbstract:Development of a novel feature extraction method denoted as OA_PCA.Introducing Optimum Allocation approach that in our innovative concept to get most representative data points from a time-window.Better performances than some existing methods. The aim of this study is to design a robust feature extraction method for the classification of multiclass EEG signals to determine valuable features from original epileptic EEG data and to discover an efficient classifier for the features. An Optimum Allocation based principal component analysis method named as OA_PCA is developed for the feature extraction from epileptic EEG data. As EEG data from different channels are correlated and huge in number, the Optimum Allocation (OA) scheme is used to discover the most favorable representatives with minimal variability from a large number of EEG data. The principal component analysis (PCA) is applied to construct uncorrelated components and also to reduce the dimensionality of the OA samples for an enhanced recognition. In order to choose a suitable classifier for the OA_PCA feature set, four popular classifiers: least square support vector machine (LS-SVM), naive bayes classifier (NB), k-nearest neighbor algorithm (KNN), and linear discriminant analysis (LDA) are applied and tested. Furthermore, our approaches are also compared with some recent research work. The experimental results show that the LS-SVM_1v1 approach yields 100% of the overall classification accuracy (OCA), improving up to 7.10% over the existing algorithms for the epileptic EEG data. The major finding of this research is that the LS-SVM with the 1v1 system is the best technique for the OA_PCA features in the epileptic EEG signal classification that outperforms all the recent reported existing methods in the literature.
