Direct Batch Generation of Optimal Eigenvectors of the Symmetric Kernel of the Discrete Hankel Transform

<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>- The development of the recently emergent discrete fractional Hankel transform (DFRHT) depends mainly on generating orthonormal eigenvectors of the kernel matrix of the discrete Hankel transform (DHT). For the DFRHT to approximate its continuous counterpart, the eigenvectors in question should approximate samples of the eigenfunctions of the Hankel transform (HT). The recently developed techniques for the generation of optimal eigenvectors of any unitary kernel matrix can be classified as either indirect (in the sense of first generating initial eigenvectors as a prerequisite for the generation of optimal ones) or direct (in the sense of not needing initial eigenvectors). Moreover, those techniques can be viewed as either batch or sequential. This paper's main objective is to assess the performance of the recently developed direct batch generation algorithms of optimal orthonormal eigenvectors of the symmetric kernel matrix of the DHT.