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ON CHANNEL ESTIMATION USING OPTIMAL TRAINING SEQUENCES IN CYCLIC-PREFIX-BASED SINGLE-CARRIER SYSTEMS WITH SPACE-TIME BLOCK-CODING
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作者 Yuan Weina Wang Ping Fan Pingzhi 《Journal of Electronics(China)》 2008年第1期28-31,共4页
In this paper, a new scheme that combines Space-Time Block-Coding (STBC) based on an Alamouti-like scheme and the Least Squares (LS) channel estimation using optimal training sequences in Cyclic-Prefix-based (CP)\Sing... In this paper, a new scheme that combines Space-Time Block-Coding (STBC) based on an Alamouti-like scheme and the Least Squares (LS) channel estimation using optimal training sequences in Cyclic-Prefix-based (CP)\Single-Carrier (SC) systems is proposed. With two transmit antennas, based on Cramer-Rao lower bound for channel estimation, it is shown that the Periodic Comple- mentary Set (PCS) is optimal over frequency-selective fading channels. Compared with the normal scheme without STBC, 3dB Mean Square Error (MSE) performance gains and fewer restrictions on the length of channel impulse response are demonstrated. 展开更多
关键词 Optimal training sequences Channel estimation Periodic complementary set (PCS) Space-Time Block-Coding (STBC)
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Further Results on the Fractional Factorial Designs Under a Conditional Model
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作者 HAN Xiaoxue HAN Bing +1 位作者 ZHAO Peng CHEN Jianbin 《Journal of Systems Science & Complexity》 2025年第5期2147-2163,共17页
The factorial design within a conditional model is utilized when the effects of one factor in a factorial experiment hold greater significance under each fixed level of another factor.This paper investigates the gener... The factorial design within a conditional model is utilized when the effects of one factor in a factorial experiment hold greater significance under each fixed level of another factor.This paper investigates the generalized minimum aberration(N,sp)-design,where each factor is s-level,with s being any prime or prime power.Via utilizing the method of complementary designs,the authors explore the design with a pair of conditional and conditioning factors.The proposed approach applies not only to regular designs but also to nonregular designs.Additionally,the findings can be extrapolated to encompass designs under the two pairs conditional model.The findings presented in this paper not only strengthen but also generalize the existing knowledge in this field. 展开更多
关键词 complementary set conditional model effect hierarchy generalized minimum aberration(GMA) orthogonal array
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General Minimum Lower-order Confounding Split-plot Designs with Important Subplot Factors
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作者 Tao SUN Sheng-li ZHAO 《Acta Mathematicae Applicatae Sinica》 2025年第2期441-455,共15页
In this paper,we consider the regular s-level fractional factorial split-plot(FFSP)designs when the subplot(SP)factors are more important.The idea of general minimum lower-order confounding criterion is applied to suc... In this paper,we consider the regular s-level fractional factorial split-plot(FFSP)designs when the subplot(SP)factors are more important.The idea of general minimum lower-order confounding criterion is applied to such designs,and the general minimum lower-order confounding criterion of type SP(SP-GMC)is proposed.Using a finite projective geometric formulation,we derive explicit formulae connecting the key terms for the criterion with the complementary set.These results are applied to choose optimal FFSP designs under the SP-GMC criterion.Some two-and three-level SP-GMC FFSP designs are constructed. 展开更多
关键词 split-plot design general minimum lower-order confounding complementary set
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Quantifying Sharpness and Nonlinearity in Neonatal Seizure Dynamics
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作者 Chien-Hung Yeh Chuting Zhang +2 位作者 Wenbin Shi Boyi Zhang Jianping An 《Cyborg and Bionic Systems》 2024年第1期770-782,共13页
The integration of multiple electrophysiological biomarkers is crucial for monitoring neonatal seizure dynamics.The present study aimed to characterize the temporal dynamics of neonatal seizures by analyzing intrinsic... The integration of multiple electrophysiological biomarkers is crucial for monitoring neonatal seizure dynamics.The present study aimed to characterize the temporal dynamics of neonatal seizures by analyzing intrinsic waveforms of epileptic electroencephalogram(EEG)signals.We proposed a complementary set of methods considering envelope power,focal sharpness changes,and nonlinear patterns of EEG signals of 79 neonates with seizures.Features derived from EEG signals were used as input to the machine learning classifier.All three characteristics were significantly elevated during seizure events,as agreed upon by all viewers(P<0.0001).Envelope power was elevated in the entire seizure period,and the degree of nonlinearity rose at the termination of a seizure event.Epileptic sharpness effectively characterizes an entire seizure event,complementing the role of envelope power in identifying its onset.However,the degree of nonlinearity showed superior discriminability for the termination of a seizure event.The proposed computational methods for intrinsic sharp or nonlinear EEG patterns evolving during neonatal seizure could share some features with envelope power.Current findings may be helpful in developing strategies to improve neonatal seizure monitoring. 展开更多
关键词 envelope powerfocal complementary set methods machine learning cl characterize temporal dynamics neonatal seizures electrophysiological biomarkers eeg signals neonatal seizures epileptic electroencephalogram eeg signalswe
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