Abstract We identify a norm-dense subspace of the dual sequence space $$l^{(p,\infty )}$$ l ( p , ∞ ) , thus closing existing gap in literature. based our approach on notion James...

Impulse radio-based ultra-wideband (UWB) communication systems allow multiple users to access channels simultaneously by assigning unique time-hopping codes to individual users, while each user’s information stream is modulated by pulse-position modulation (PPM). However, transmitted signals undergo fading from a number of propagation paths in a dense multipath environment and meanwhile suffer ...

Compactification of a space X is compact containing as dense subspace. Magills construction for compactications fixed Tychonoff through partitions applied to derive various spaces (X;T), with set and variation in topologies 'T'. Some possible extensions mappings are obtained this regard. In extension topological group, the inverse operation should be extendable homeomorphically from base group....

Finding clusters in high dimensional data is a challenging task as the high dimensional data comprises hundreds of attributes. Subspace clustering is an evolving methodology which, instead of finding clusters in the entire feature space, it aims at finding clusters in various overlapping or non-overlapping subspaces of the high dimensional dataset. Density based subspace clustering algorithms t...

We address the problem of partial symmetry detection, i.e., the identification of building blocks a complex shape is composed of. Previous techniques identify parts that relate to each other by simple rigid mappings, similarity transforms, or, more recently, intrinsic isometries. Our approach generalizes the notion of partial symmetries to more general deformations. We introduce subspace symmet...

Let A be a bounded self-adjoint operator on a separable Hilbert space H and H0 ⊂ H a closed invariant subspace of A. Assuming that H0 is of codimension 1, we study the variation of the invariant subspace H0 under bounded self-adjoint perturbations V of A that are off-diagonal with respect to the decomposition H = H0 ⊕H1. In particular, we prove the existence of a oneparameter family of dense no...

Examples: 1) Local spectral radius r(T, x) of an operator T at a point x ∈ X can be defined by r(T, x) = lim supk→∞ ‖T kx‖1/k, i.e. it is a quantity defined in terms of B. The local spectral radius plays an important role in the local spectral theory. 2) As an analogy to the local spectral radius for the set of all polynomials can be considered the local capacity (see later). 3) The invariant s...

this paper considers the automatic design of fuzzy rule-basedclassification systems based on labeled data. the classification performance andinterpretability are of major importance in these systems. in this paper, weutilize the distribution of training patterns in decision subspace of each fuzzyrule to improve its initially assigned certainty grade (i.e. rule weight). ourapproach uses a punish...

Noise significantly affects cluster quality. Conventional clustering methods hardly detect clusters in a data set containing a large amount of noise. Projected clustering sheds light on identifying correlation clusters in such a data set. In order to exclude noise points which are usually scattered in a subspace, data points are projected to form dense areas in the subspace that are regarded as...

This paper designs and evaluates a variant of CoSaMP algorithm, for recovering the sparse signal s from the compressive measurement ( ) v Uw s   given a fixed lowrank subspace spanned by U. Instead of firstly recovering the full vector then separating the sparse part from the structured dense part, the proposed algorithm directly works on the compressive measurement to do the separation. We i...