Design of GaN HEMTs for Power Switching Operation

A model based on the key parameters of the device, such as the 2DEG carrier concentration and its mobility, as well as the active area geometry, will be presented and discussed

Self-gated respiratory-resolved 5D Flow MRI using the 3D spiral phyllotaxis trajectory

International audienc

All Invariant Moments of the Wishart Distribution

In this paper, we compute moments of a Wishart matrix variate "U" of the form E ("Q"("U")) where "Q"("u") is a polynomial with respect to the entries of the symmetric matrix "u", invariant in the sense that it depends only on the eigenvalues of the matrix "u". This gives us in particular the expected value of any power of the Wishart matrix "U" or its inverse "U"-super- -  1. For our proofs, we do not rely on traditional combinatorial methods but rather on the interplay between two bases of the space of invariant polynomials in "U". This means that all moments can be obtained through the multiplication of three matrices with known entries. Practically, the moments are obtained by computer with an extremely simple Maple program. Copyright 2004 Board of the Foundation of the Scandinavian Journal of Statistics..