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  2. Image (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Image_(mathematics)

    The preimage of an output value is the set of input values that produce . More generally, evaluating f {\displaystyle f} at each element of a given subset A {\displaystyle A} of its domain X {\displaystyle X} produces a set, called the " image of A {\displaystyle A} under (or through) f {\displaystyle f} ".

  3. Fiber (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Fiber_(mathematics)

    If and are the domain and image of , respectively, then the fibers of are the sets in {():} = {{: =}:}which is a partition of the domain set .Note that must be restricted to the image set of , since otherwise () would be the empty set which is not allowed in a partition.

  4. Proper map - Wikipedia

    en.wikipedia.org/wiki/Proper_map

    Some authors call a function : between two topological spaces proper if the preimage of every compact set in is compact in . Other authors call a map f {\displaystyle f} proper if it is continuous and closed with compact fibers ; that is if it is a continuous closed map and the preimage of every point in Y {\displaystyle Y} is compact .

  5. σ-algebra - Wikipedia

    en.wikipedia.org/wiki/Σ-algebra

    The family consisting only of the empty set and the set , called the minimal or trivial σ-algebra over . The power set of X , {\displaystyle X,} called the discrete σ-algebra . The collection { ∅ , A , X ∖ A , X } {\displaystyle \{\varnothing ,A,X\setminus A,X\}} is a simple σ-algebra generated by the subset A . {\displaystyle A.}

  6. Lebesgue measure - Wikipedia

    en.wikipedia.org/wiki/Lebesgue_measure

    A subset of R n is a null set if, for every ε > 0, it can be covered with countably many products of n intervals whose total volume is at most ε. All countable sets are null sets. If a subset of R n has Hausdorff dimension less than n then it is a null set with respect to n-dimensional Lebesgue measure.

  7. Convex set - Wikipedia

    en.wikipedia.org/wiki/Convex_set

    Equivalently, a convex set or a convex region is a set that intersects every line in a line segment, single point, or the empty set. [1] [2] For example, a solid cube is a convex set, but anything that is hollow or has an indent, for example, a crescent shape, is not convex. The boundary of a convex set in the plane is always a convex curve.

  8. Naive Set Theory (book) - Wikipedia

    en.wikipedia.org/wiki/Naive_Set_Theory_(book)

    This schema is used in 4.-7. below to cut down the set that is stated to exist to the set containing precisely the intended elements, rather than some larger set with extraneous elements. For example, the axiom of pairing applied to the sets A {\displaystyle A} and B {\displaystyle B} only guarantees there is some set X {\displaystyle X} such ...

  9. Kernel (set theory) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(set_theory)

    Conversely, if is a Hausdorff space and ⁡ is a closed set, then the coimage of , if given the quotient space topology, must also be a Hausdorff space. A space is compact if and only if the kernel of every family of closed subsets having the finite intersection property (FIP) is non-empty; [ 4 ] [ 5 ] said differently, a space is compact if ...