Basic helix-loop-helix （bHLH） transcription factors regulate the differentiation of various tissues in a vast diversity of species. The bHLH protein Atonal was first identified as a proneural gene involved in the fo...Basic helix-loop-helix （bHLH） transcription factors regulate the differentiation of various tissues in a vast diversity of species. The bHLH protein Atonal was first identified as a proneural gene involved in the formation of mechanosensory cells and photoreceptor cells in Drosophila （larman et al., 1993, 1994）. Atonal is expressed in sensory organ precursors and is required and sufficient for the development of chordotonal organs （Jar- man et al., 1993）. Moreover, Atonal expression is observed in the developing eye and is essential for the differentiation of R8 photoreceptors, which are the first photoreceptors that appear during development. Atonal is not involved in the formation of other photoreceptors （R1-R7） directly. However, R8 photore- ceptors recruit other photoreceptors from the surrounding cells （Jarman et al., 1994）.展开更多
Extracting nonlinear governing equations from noisy data is a central challenge in the analysis of complicated nonlinear behaviors.Despite researchers follow the sparse identification nonlinear dynamics algorithm(SIND...Extracting nonlinear governing equations from noisy data is a central challenge in the analysis of complicated nonlinear behaviors.Despite researchers follow the sparse identification nonlinear dynamics algorithm(SINDy)rule to restore nonlinear equations,there also exist obstacles.One is the excessive dependence on empirical parameters,which increases the difficulty of data pre-processing.Another one is the coexistence of multiple coefficient vectors,which causes the optimal solution to be drowned in multiple solutions.The third one is the composition of basic function,which is exclusively applicable to specific equations.In this article,a local sparse screening identification algorithm(LSSI)is proposed to identify nonlinear systems.First,we present the k-neighbor parameter to replace all empirical parameters in data filtering.Second,we combine the mean error screening method with the SINDy algorithm to select the optimal one from multiple solutions.Third,the time variable t is introduced to expand the scope of the SINDy algorithm.Finally,the LSSI algorithm is applied to recover a classic ODE and a bi-stable energy harvester system.The results show that the new algorithm improves the ability of noise immunity and optimal parameters identification provides a desired foundation for nonlinear analyses.展开更多
基金supported by grants from the Ministry of Education,Culture,Sports,Science and Technology in Japan and Naito Foundation to TCthe Japan Society for the Promotion of Science to MO and TC
文摘Basic helix-loop-helix （bHLH） transcription factors regulate the differentiation of various tissues in a vast diversity of species. The bHLH protein Atonal was first identified as a proneural gene involved in the formation of mechanosensory cells and photoreceptor cells in Drosophila （larman et al., 1993, 1994）. Atonal is expressed in sensory organ precursors and is required and sufficient for the development of chordotonal organs （Jar- man et al., 1993）. Moreover, Atonal expression is observed in the developing eye and is essential for the differentiation of R8 photoreceptors, which are the first photoreceptors that appear during development. Atonal is not involved in the formation of other photoreceptors （R1-R7） directly. However, R8 photore- ceptors recruit other photoreceptors from the surrounding cells （Jarman et al., 1994）.
基金The work was supported by the National Science Foundation of China(grant nos.11772218 and 11872044)China-UK NSFC-RS Joint Project(grant nos.11911530177 in China and IE181496 in the UK)Tianjin Research Program of Application Foundation and Advanced Technology(grant no.17JCYBJC18900).
文摘Extracting nonlinear governing equations from noisy data is a central challenge in the analysis of complicated nonlinear behaviors.Despite researchers follow the sparse identification nonlinear dynamics algorithm(SINDy)rule to restore nonlinear equations,there also exist obstacles.One is the excessive dependence on empirical parameters,which increases the difficulty of data pre-processing.Another one is the coexistence of multiple coefficient vectors,which causes the optimal solution to be drowned in multiple solutions.The third one is the composition of basic function,which is exclusively applicable to specific equations.In this article,a local sparse screening identification algorithm(LSSI)is proposed to identify nonlinear systems.First,we present the k-neighbor parameter to replace all empirical parameters in data filtering.Second,we combine the mean error screening method with the SINDy algorithm to select the optimal one from multiple solutions.Third,the time variable t is introduced to expand the scope of the SINDy algorithm.Finally,the LSSI algorithm is applied to recover a classic ODE and a bi-stable energy harvester system.The results show that the new algorithm improves the ability of noise immunity and optimal parameters identification provides a desired foundation for nonlinear analyses.
