In mathematical analysis, the Minkowski inequality establishes that the Lp spaces are normed vector spaces. Let S be a measure space, let 1 ≤ p ≤ ∞ and let f and g be elements of Lp(S). Then f + g is in Lp(S), and we have the triangle inequality
with equality for 1 < p < ∞ if and only if f and g are positively linearly dependent, i.e., f = g for some ≥ 0. Here, the norm is given by:
if p < ∞, or in the case p = ∞ by the essential supremum
The Minkowski inequality is the triangle inequality in Lp(S). In fact, it is a special case of the more general fact
where it is easy to see that the right-hand side satisfies the triangular inequality.
Like Hölder's inequality, the Minkowski inequality can be specialized to sequences and vectors by using the counting measure:
for all real (or complex) numbers x1, ..., xn, y1, ..., yn and where n is the cardinality of S (the number of elements in S).
Read more about Minkowski Inequality: Proof, Minkowski's Integral Inequality
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