1,915 research outputs found

    Multiscale Representations for Manifold-Valued Data

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    We describe multiscale representations for data observed on equispaced grids and taking values in manifolds such as the sphere S2S^2, the special orthogonal group SO(3)SO(3), the positive definite matrices SPD(n)SPD(n), and the Grassmann manifolds G(n,k)G(n,k). The representations are based on the deployment of Deslauriers--Dubuc and average-interpolating pyramids "in the tangent plane" of such manifolds, using the ExpExp and LogLog maps of those manifolds. The representations provide "wavelet coefficients" which can be thresholded, quantized, and scaled in much the same way as traditional wavelet coefficients. Tasks such as compression, noise removal, contrast enhancement, and stochastic simulation are facilitated by this representation. The approach applies to general manifolds but is particularly suited to the manifolds we consider, i.e., Riemannian symmetric spaces, such as Sn−1S^{n-1}, SO(n)SO(n), G(n,k)G(n,k), where the ExpExp and LogLog maps are effectively computable. Applications to manifold-valued data sources of a geometric nature (motion, orientation, diffusion) seem particularly immediate. A software toolbox, SymmLab, can reproduce the results discussed in this paper

    Functional central limit theorems for rough volatility

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    We extend Donsker's approximation of Brownian motion to fractional Brownian motion with Hurst exponent H∈(0,1)H \in (0,1) and to Volterra-like processes. Some of the most relevant consequences of our `rough Donsker (rDonsker) Theorem' are convergence results for discrete approximations of a large class of rough models. This justifies the validity of simple and easy-to-implement Monte-Carlo methods, for which we provide detailed numerical recipes. We test these against the current benchmark Hybrid scheme \cite{BLP15} and find remarkable agreement (for a large range of values of~HH). This rDonsker Theorem further provides a weak convergence proof for the Hybrid scheme itself, and allows to construct binomial trees for rough volatility models, the first available scheme (in the rough volatility context) for early exercise options such as American or Bermudan.Comment: 30 pages, 11 figure
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