Isometric multipliers ofL p (G, X)

Let G be a locally compact group with a fixed right Haar measure andX a separable Banach space. LetL ^p (G, X) be the space of X-valued measurable functions whose norm-functions are in the usualL ^p . A left multiplier ofL ^p (G, X) is a bounded linear operator onB ^p (G, X) which commutes with all left translations. We use the characterization of isometries ofL ^p (G, X) onto itself to characterize the isometric, invertible, left multipliers ofL ^p (G, X) for 1 ≤p ∞,p ≠ 2, under the assumption thatX is not thel ^p -direct sum of two non-zero subspaces. In fact we prove that ifT is an isometric left multiplier ofL ^p (G, X) onto itself then there existsa y ∃ G and an isometryU ofX onto itself such thatTf(x) = U (R _y f)(x). As an application, we determine the isometric left multipliers of L¹ ∩L ^p (G, X) and L¹ ∩C ₀ (G, X) whereG is non-compact andX is not the l^p-direct sum of two non-zero subspaces. If G is a locally compact abelian group andH is a separable Hubert space, we define where г is the dual group of G. We characterize the isometric, invertible, left multipliers ofA ^p (G, H), provided G is non-compact. Finally, we use the characterization of isometries ofC(G, X) for G compact to determine the isometric left multipliers ofC(G, X) providedX ^* is strictly convex.     

Characterization of Compact Support of Fourier Transform for Orthonormal Wavelets of L^2（R^d）

Let{ψμ} be an orthonormal wavelet of L^2（R^d） and the support of a whole of its Fourier transform be Uμsupp{ψμ}=Пi=1^d[Ai, Di]-Пi=1^d（Bi, Ci）, Ai≤Bi≤Ci≤Di. Under the weakest condition that each │ψμ│, is continuous for ω ∈ δ（Пi=1^d[Ai, Di]）, a characterization of the above support of a whole is given.     

基于方向-频率分解的旋转不变性纹理分类

提出了一种用于纹理分类的旋转不变性特征提取的新算法.该算法是将一定大小的图像进行二维傅里叶变换;其次在变换后的图像中央选择一个圆盘区域,并在方向[0°,180°]内进行等间隔角度频率抽样,实现方向分解,使用一组复Morlet小波对每个方向上的映射切片进行小波变换,从而实现多通道频率分解;在各个频率通道中计算均值和方差作为特征,并利用线性回归模型计算频率通道之间的关系特征;将特征沿方向进行一维傅里叶变换并取其幅值,从而得到旋转不变性特征.实验结果表明所提取的特征具有较好的旋转不变性,与其它算法相比具有更好的分类性能,并且对无旋转纹理分类也能产生较好的分类结果.     

Wavelet estimations for mixed densities under multiplicative censoring

Using compactly supported wavelets, Chaubey et al consider L²-risk estimation for mixed density under multiplicative censoring (Chaubey YP, Chesneau C, Doosti H. Adaptive wavelet estimation of a density from mixtures under multiplicative censoring. Statistics, 2015, 49: 638-659). In this paper, we try to discuss L^p-risk (1 ≤ p<∞) estimation for that statistical model of the linear and nonlinear wavelet estimators respectively. Our results can be seen as an extension of the work of Chaubey et al.     

Bilinear paraproducts revisited

Boundedness properties for bilinear paraproducts on several function spaces are presented. The methods are based on the realization of paraproducts as bilinear Calderón‐Zygmund operators and the molecular character‐ization of function spaces. This provides a unified approach for the study of paraproducts, recovering some know results and establishing several new (© 2010 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Interpolatory Hermite splines on rectangular domains

Based on Bittner and Urban’s construction of interpolatory multiwavelets [Kai Bittner, Karsten Urban, On interpolatory divergence-free wavelets, Math. Comput. 76 (258) (2007) 903-929], we use the truncation method to obtain interpolatory multiwavelets on rectangular domains in this paper. In addition, the characterization for the corresponding functional spaces is given.     

Coupled Galerkin and parameterization methods for optimal control of discretely connected parallel beams

Galerkin and wavelet methods for optimal boundary control of a couple of discretely connected parallel beams are proposed. First, the problem with boundary controls is converted into a problem with distributed controls. The problem is, then, reduced by a Galerkin-based approach into determining the optimal control of a linear time-invariant lumped parameter system, which will be solved by a wavelet-based method using Legendre wavelets. The integration-operational matrix and Kronecker product are utilized to significantly simplify the optimization problem into a system of linear equations. A numerical example is presented to demonstrate the applicability and the efficiency of the proposed method.     

Magnetic resonance image reconstruction using trained geometric directions in 2D redundant wavelets domain and non-convex optimization

Reducing scanning time is significantly important for MRI. Compressed sensing has shown promising results by undersampling the k-space data to speed up imaging. Sparsity of an image plays an important role in compressed sensing MRI to reduce the image artifacts. Recently, the method of patch-based directional wavelets (PBDW) which trains geometric directions from undersampled data has been proposed. It has better performance in preserving image edges than conventional sparsifying transforms. However, obvious artifacts are presented in the smooth region when the data are highly undersampled. In addition, the original PBDW-based method does not hold obvious improvement for radial and fully 2D random sampling patterns. In this paper, the PBDW-based MRI reconstruction is improved from two aspects: 1) An efficient non-convex minimization algorithm is modified to enhance image quality; 2) PBDW are extended into shift-invariant discrete wavelet domain to enhance the ability of transform on sparsifying piecewise smooth image features. Numerical simulation results on vivo magnetic resonance images demonstrate that the proposed method outperforms the original PBDW in terms of removing artifacts and preserving edges.     

Quantum double constructions for compact quantum group

For a non-degenerate pair of compact quantum groups, we first construct the quantum double as an algebraic compact quantum group in an algebraic framework. Then by adopting some completion procedure, we give the universal and reduced quantum double constructions in the correspondence C＊-algebraic settings, which generalize Drinfeld＇s quantum double construction and yield new C＊-algebraic compact quantum groups.