Abstract

A common approach for describing classes of functions and probability measures on a topological space X\mathcal{X} is to construct a suitable map ΦΦ from X\mathcal{X} into a vector space, where linear methods can be applied to address both problems. The case where X\mathcal{X} is a space of paths [0,1]→Rn[0,1] \to \mathbb{R}^n and ΦΦ is the path signature map has received much attention in stochastic analysis and related fields. In this article we develop a generalized ΦΦ for the case where X\mathcal{X} is a space of maps [0,1]d→Rn[0,1]^d \to \mathbb{R}^n for any d∈Nd \in \mathbb{N}, and show that the map ΦΦ generalizes many of the desirable algebraic and analytic properties of the path signature to d≥2d \ge 2. The key ingredient to our approach is topological; in particular, our starting point is a generalisation of K-T Chen's path space cochain construction to the setting of cubical mapping spaces.

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