Supported by the Natural Science Foundation of China(10501026,60675010,10971251)
We study the approximation of functions from anisotropic Sobolev classes b(WpR([0, 1]d)) and HSlder-Nikolskii classes B(HPr([0, 1]d)) in the Lq ([0, 1]d) norm with q 〈 p in the quantum model of computation....
Supported by National Natural Science Foundation of China (No. 60872161, 10501026, 60675010 and 10626029);Natural Science Foundation of Tianjin (No. 08JCYBJC09600);China Postdoctoral Science Foundation ( No. 20070420708).
Nonlinear m-term approximation plays an important role in machine learning, signal processing and statistical estimating. In this paper by means of a nondecreasing dominated function, a greedy adaptive compression num...
supported by the National Natural Science Foundation of China (Grant Nos. 10501026, 60675010,10626029 and 60572113);the China Postdoctoral Science Foundation (Grant No. 20070420708)
We study the approximation of the imbedding of functions from anisotropic and generalized Sobolev classes into L q ([0, 1]d) space in the quantum model of computation. Based on the quantum algorithms for approximation...
National Natural Science Foundation of China (No60572113,No10501026) and Liuhui Center for Applied Mathematics
Signals are often of random character since they cannot bear any information if they are predictable for any time t, they are usually modelled as stationary random processes .On the other hand, because of the inertia ...
Supported by National Natural Science Foundation of China (Grant Nos. 10261007 and 10501026)Tianyuan Fund for Mathematics (Grant No.10426020) and the fund of Nankai University
We study the restricted Monte Carlo integration error for anisotropie Sobolev classes. Results prove that with O(log2 n ) random bits we have the optimal order for the n-th minimal Monte Carlo integration error with...