Math 2.0

example

p-metric on R^n

Example

Let n≥1n \ge 1 be an integer and let p≥1p \ge 1 be a real number. For x=(x1,…,xn)x = (x_1, \ldots, x_n) and y=(y1,…,yn)y = (y_1, \ldots, y_n) in Rn\mathbb{R}^n, let dp(x,y)=(∑i=1n∣xi−yi∣p)1/p.d_p(x, y) = \left( \sum_{i=1}^{n} |x_i - y_i|^p \right)^{1/p}. Then dpd_p is a metric on Rn\mathbb{R}^n.

Remarks

The triangle inequality for dpd_p is the Minkowski inequality. For p=1p = 1 it is the taxicab metric, and for p=2p = 2 it is the Euclidean metric. For 0<p<10 < p < 1, the same formula does not give a metric when n≥2n \ge 2: the triangle inequality fails. The metric dpd_p comes from the p-norm: dp(x,y)=∥x−y∥pd_p(x, y) = \|x - y\|_p.

Explanations

L1 human

The p-metrics form a family of ways to combine the differences of the coordinates into one distance. A larger pp gives more weight to the largest difference, and for very large pp the distance is close to the sup metric.

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Sources

  1. Web https://en.wikipedia.org/wiki/Lp_space, The p-norm in finite dimensions