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Approximation of weak sense stationary stochastic processes from local averages 被引量:7
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作者 Zhan-jie SONG Wen-chang SUN +1 位作者 Shou-yuan YANG Guang-wen ZHU 《Science China Mathematics》 SCIE 2007年第4期457-463,共7页
We show that a weak sense stationary stochastic process can be approximated by local averages. Explicit error bounds are given. Our result improves an early one from Splettst?sser.
关键词 sampling theorem weak sense stationary stochastic processes local averages average sampling 42C15 60G10 94A20
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CONSTRUCTION OF POLYNOMIAL MATRIX USING BLOCK COEFFICIENT MATRIX REPRESENTATION AUTO-REGRESSIVE MOVING AVERAGE MODEL FOR ACTIVELY CONTROLLED STRUCTURES 被引量:1
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作者 李春祥 周岱 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2004年第6期661-667,共7页
The polynomial matrix using the block coefficient matrix representation auto-regressive moving average(referred to as the PM-ARMA)model is constructed in this paper for actively controlled multi-degree-of-freedom(MDOF... The polynomial matrix using the block coefficient matrix representation auto-regressive moving average(referred to as the PM-ARMA)model is constructed in this paper for actively controlled multi-degree-of-freedom(MDOF)structures with time-delay through equivalently transforming the preliminary state space realization into the new state space realization.The PM-ARMA model is a more general formulation with respect to the polynomial using the coefficient representation auto-regressive moving average(ARMA)model due to its capability to cope with actively controlled structures with any given structural degrees of freedom and any chosen number of sensors and actuators.(The sensors and actuators are required to maintain the identical number.)under any dimensional stationary stochastic excitation. 展开更多
关键词 actively controlled MDOF structures stationary stochastic processes polynomial matrix auto-regressive moving average
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