Programmers develop problem solutions in an abstract idea space, where they can easily visualise different views of the solution. However, conventional programs exist in sequential text space, where these different views often become inextricably tangled. We reject the text-based single-sequence structure-which many visual programming languages have heedlessly adopted-in favour of a hyperspatia...

We introduce a two-stage analysis of color spectra. In the first processing stage, correlation with the first eigenvector of a spectral database is used to measure the intensity of a color spectrum. In the second step, a perspective projection is used to map the color spectrum to the hyperspace of spectra with first eigenvector coefficient equal to unity. The location in this hyperspace describ...

It is shown that the family of all homogeneous continua in hyperspace subcontinua any finite-dimensional Euclidean cube or Hilbert an analytic subspace which contains a topological copy linear space c0={(xk)∈Rω:lim⁡xk=0} as closed subset.

The symbol S( X ) denotes the hyperspace of finite unions convergent sequences in a Hausdor˛ space . This hyper-space is endowed with Vietoris topology. First all, we give characterization sequence ). Then consider some cardinal invariants on ), and compare character, pseudocharacter, sn-character, so-character, network weight cs-network S ( corresponding function Moreover, rank k -diagonal 2 s...

We propose an on-board selection scheme for aerial and space images, based on linear feature detection in a feature hyperspace. The detection task is performed by means of the Radon transform (RT) and the wavelet transform; a fast algorithm for the RT computation is described, and counteractions against the discretization errors are proposed. A new, wavelet-based algorithm is introduced, which ...