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On orlicz sequence spaces

Israel Journal of Mathematics, 1971
It is proved that every Orlicz sequence space contains a subspace isomorphic to somel p . The question of uniqueness of symmetric bases in Orlicz sequence spaces is investigated.
Lindenstrauss, J., Tzafriri, L.
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Finitary sequence spaces

Mathematical Logic Quarterly, 1993
AbstractThis paper studies the metric structure of the space Hr of absolutely summable sequences of real numbers with at most r nonzero terms. Hr is complete, and is located and nowhere dense in the space of all absolutely summable sequences. Totally bounded and compact subspaces of Hr are characterized, and large classes of located, totally bounded ...
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Convergence in Sequence Spaces

Proceedings of the Edinburgh Mathematical Society, 1958
In a perfect sequence space α, on which a norm is defined, we can consider three types of convergence, namely projective convergence, strong projective convergence and distance convergence. In the space σ∞, when distance is defined in the usual way, the last two types of convergence coincide and are distinct from projective convergence ((2), p.
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BA SEQUENCE SPACES

Acta Mathematica Scientia, 1992
Summary: We introduce and discuss the Ba sequence spaces. A characteristic of separability of Ba sequence space is given. Other important properties of Ba sequence spaces are discussed.
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On Orlicz sequence spaces. II

Israel Journal of Mathematics, 1972
It is proved that the set ofp's such thatlp is isomorphic to a subspace of a given Orlicz spacelFforms an interval. Some examples and properties of minimal Orlicz sequence spaces are presented. It is proved that an Orlicz function space (different froml2) is not isomorphic to a subspace of an Orlicz sequence space.
Lindenstrauss, J., Tzafriri, L.
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Imaging sequence space

Nature, 1994
Digital imaging spectrophotometers can simultaneously measure the spectra of hundreds of features in a two-dimensional scene. While a variety of applications can be anticipated, a colorimetric analysis of mutants expressing pigmented proteins has already led to the development of efficient algorithms for optimizing combinatorial mutagenesis.
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