Linked from

The 17 pages that link to Lp space, each with the reason it gives.

• Hilbert spaceCompared with: For p other than 2, the usual Lp norm generally does not arise from an inner product.

• Measure theoryRelated: These spaces organize functions by integrability and support much of analysis.

• Normed vector spaceBroader topic: Its norms measure the size of functions or sequences across a range of applications.

• Hölder's inequalityNarrower topic: Hölder bounds pairings between functions in conjugate Lᵖ spaces.

• Euclidean normNarrower topic: Its parameter selects the Euclidean norm at p equal to two and other familiar norms at different values.

• Functional analysisBroader topic: These spaces provide the main settings for convergence and integrability estimates.

• Almost everywhereRelated: Its elements are equivalence classes, not individual pointwise function values.

• Supremum normNarrower topic: Finite-p norms provide a broader family of alternatives to the supremum-based measure.

• Measure spaceRelated: Its definition depends on integrating powers over a measure space.

• Henri LebesgueRelated: Lebesgue integration defines the norms that make these function spaces possible.

• Minkowski inequalityNarrower topic: Minkowski proves that the Lp expression is a norm for p ≥ 1.

• Parallelogram lawRelated: For p other than two, its usual norm generally fails the parallelogram law.

• Hardy–Littlewood maximal functionRelated: Its norms provide the natural scale for maximal-operator bounds.

• Approximation theoryRelated: Lp norms provide common ways to measure average approximation error.

• Young's inequality for productsRelated: Young's bound controls products of functions whose powers are integrable.

• Hilbert transformRelated: For 1 < p < ∞, the transform extends to a bounded operator on these spaces.

• Dvoretzky's theoremRelated: Its changing geometry across p illustrates how ambient norms shape the size of Euclidean sections.