Work

Exact simulation of noncircular or improper complex-valued stationary Gaussian processes using circulant embedding

Year: 2016

Type: conference-paper

Abstract: This paper provides an algorithm for simulating improper (or noncircular) complex-valued stationary Gaussian processes. The technique utilizes recently developed methods for multi-variate Gaussian processes from the circulant embedding literature. The method can be performed in O(n log2n) operations, where n is the length of the desired sequence. The method is exact, except when eigenvalues of prescribed circulant matrices are negative. We evaluate the performance of the algorithm empirically, and provide a practical example where the method is guaranteed to be exact for all n, with an improper fractional Gaussian noise process.

Source: IEEE International Workshop on Machine Learning for Signal Processing (MLSP)

DOI: 10.1109/mlsp.2016.7738840

Authors: Adam M. Sykulski, Donald B. Percival

Institutions: University College London, University of Washington, University of Washington Applied Physics Laboratory

Language: English

Topic: Matrix Theory and Algorithms

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2394909248

FWCI: 1.658

Cites: 26

Cited by: 10

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