The fixed-point algorithm and infomax algorithm are two of the most popular algorithms in independent component analysis(ICA).However,it is hard to take both stability and speed into consideration in processing functi...The fixed-point algorithm and infomax algorithm are two of the most popular algorithms in independent component analysis(ICA).However,it is hard to take both stability and speed into consideration in processing functional magnetic resonance imaging(fMRI)data.In this paper,an optimization model for ICA is presented and an improved fixed-point algorithm based on the model is proposed.In the new algorithms a small step size is added to increase the stability.In order to accelerate the convergence,an improvement on Newton method is made,which makes cubic convergence for the new algorithm.Applying the algorithm and two other algorithms to invivo fMRI data,the results show that the new algorithm separates independent components stably,which has faster convergence speed and less computation than the other two algorithms.The algorithm has obvious advantage in processing fMRI signal with huge data.展开更多
Biological inspirations are good design mimicry resources. This paper proposes a function based approach for modeling and transformation of bio-inspiration design knowledge. A general functional modeling method for bi...Biological inspirations are good design mimicry resources. This paper proposes a function based approach for modeling and transformation of bio-inspiration design knowledge. A general functional modeling method for biological domain and engineering domain design knowledge is introduced. Functional similarity based bio-inspiration transformation between biological domain and engineering domain is proposed. The biological function topology transfer and analog solution recomposition are also discussed in this paper.展开更多
文摘The fixed-point algorithm and infomax algorithm are two of the most popular algorithms in independent component analysis(ICA).However,it is hard to take both stability and speed into consideration in processing functional magnetic resonance imaging(fMRI)data.In this paper,an optimization model for ICA is presented and an improved fixed-point algorithm based on the model is proposed.In the new algorithms a small step size is added to increase the stability.In order to accelerate the convergence,an improvement on Newton method is made,which makes cubic convergence for the new algorithm.Applying the algorithm and two other algorithms to invivo fMRI data,the results show that the new algorithm separates independent components stably,which has faster convergence speed and less computation than the other two algorithms.The algorithm has obvious advantage in processing fMRI signal with huge data.
基金the National Basic Research Program(973)of China(Nos.2011CB707503 and2011CB013305)the National Natural Science Foundation of China(Nos.51075262,51305260,51275293,51121063,50575142 and 51005148)+4 种基金the"ShuGuang"Project of Shanghai Municipal Education Commissionand Shanghai Education Development Foundation(No.12SG14)the Project of Shanghai Committee of Science and Technology(Nos.11JC1406100,13111102800 and 11BA1405300)the National KeyScientific Instruments and Equipment Development Program of China(Nos.2013YQ03065105 and2011YQ030114)the Program for New Century Excellent Talents in University(No.NCET-08-0361)the National High Technology Research and DevelopmentProgram(863)of China(No.2008AA04Z113)
文摘Biological inspirations are good design mimicry resources. This paper proposes a function based approach for modeling and transformation of bio-inspiration design knowledge. A general functional modeling method for biological domain and engineering domain design knowledge is introduced. Functional similarity based bio-inspiration transformation between biological domain and engineering domain is proposed. The biological function topology transfer and analog solution recomposition are also discussed in this paper.
