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 log2 n) 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
this paper, we will describe a convenient method for generating these random processes and fields e#...
In this paper novel simulation methods are provided for the generalised inverse Gaussian (GIG) L\'{e...
In complex-valued signal processing, estimation algorithms require complete knowledge (or accurate e...
This paper provides an algorithm for simulating improper (or noncircular) complex-valued stationary ...
<p>This paper is concerned with the study of the embedding circulant matrix method to simulate stati...
Circulant embedding is a technique that has been used to generate realizations from certain real-val...
<div><p>When generating Gaussian stationary random fields, a standard method based on circulant matr...
The circulant embedding method for generating statistically exact simulations of time series from ce...
Random fields are families of random variables, indexed by a d-dimensional parameter x with d> 1....
We demonstrate that the fast and exact Davies–Harte algorithm is valid for simulating a certain clas...
International audienceMathematical justifications are given for a Monte Carlo simulation technique b...
A new simulation algorithm is developed for generating non-Gaussian processes with a specified margi...
Mathematical justifications are given for a simulation technique of multivariate nonGaussian random ...
We develop some simple simulation algorithms for CIR and Wishart processes. We investigate rigorousl...
Abstract We proposed a new iterative power and amplitude correction (IPAC) algorithm to simulate non...
this paper, we will describe a convenient method for generating these random processes and fields e#...
In this paper novel simulation methods are provided for the generalised inverse Gaussian (GIG) L\'{e...
In complex-valued signal processing, estimation algorithms require complete knowledge (or accurate e...
This paper provides an algorithm for simulating improper (or noncircular) complex-valued stationary ...
<p>This paper is concerned with the study of the embedding circulant matrix method to simulate stati...
Circulant embedding is a technique that has been used to generate realizations from certain real-val...
<div><p>When generating Gaussian stationary random fields, a standard method based on circulant matr...
The circulant embedding method for generating statistically exact simulations of time series from ce...
Random fields are families of random variables, indexed by a d-dimensional parameter x with d> 1....
We demonstrate that the fast and exact Davies–Harte algorithm is valid for simulating a certain clas...
International audienceMathematical justifications are given for a Monte Carlo simulation technique b...
A new simulation algorithm is developed for generating non-Gaussian processes with a specified margi...
Mathematical justifications are given for a simulation technique of multivariate nonGaussian random ...
We develop some simple simulation algorithms for CIR and Wishart processes. We investigate rigorousl...
Abstract We proposed a new iterative power and amplitude correction (IPAC) algorithm to simulate non...
this paper, we will describe a convenient method for generating these random processes and fields e#...
In this paper novel simulation methods are provided for the generalised inverse Gaussian (GIG) L\'{e...
In complex-valued signal processing, estimation algorithms require complete knowledge (or accurate e...