Parabolic scaling and anisotropic dilation form the core of famous multi-resolution transformations such as curvelet and shearlet, which are widely used in signal processing applications like denoising. These non-adaptive geometrical wavelets are commonly used to extract structures and geometrical features of multi-dimensional signals and preserve them in noise removal treatments. In discrete s...

the space now known as complete erdos space ec was introduced by paul erdos in 1940 as the closed subspace of the hilbert space ?2 consisting of all vectors such that every coordinate is in the convergent sequence {0} ? { 1 n : n ? n}. in a solution to a problem posed by lex g. oversteegen we present simple and useful topological characterizations of ec. as an application we determine the ...

In this paper, a sparse representation based manifold learning method is proposed. The construction of the graph manifold in high dimensional space is the most important step of the manifold learning methods that is divided into local and gobal groups. The proposed graph manifold extracts local and global features, simultanstly. After construction the sparse representation based graph manifold,...

SAR imaging systems are as a complement to passive remote sensing but the process of image formation in this systems is so complex So that the final image in the system is formed after the three basic steps: raw data acquisition, forming the signal space and image space. In addition, various factors within the system and outside the system are involved in the information that recorded by SAR, s...