The aliasing‐phenomenon in visual terms
Bibliographic Data
| ID | 10142154 |
|---|---|
| Authors | Hermann Singer (University of Konstanz, corresponding author) |
| Year | 1992 |
| Volume | 17 |
| Issue | 1 |
| Pages | 39-49 |
| Publication date | 1992-05-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Mathematical Sociology (JOURNAL) |
| Journal identifiers | ISSN: 0022-250X • E-ISSN: 1545-5874 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/0022250x.1992.9990097 |
| OpenAlex | W2018633819 |
| Language | EN |
| Citations received | 3 |
| References cited | 7 |
In a recent paper it was shown that the aliasing phenomenon, which leads to a severe identification problem in the estimation of stochastic differential equations, can be overcome by using a polygonal (or higher) approximation for the time paths of the exogenous variables. This work attempts to visualize the problem and presents several simulated trajectories of a continuous time AR(2)‐process (Ornstein‐Uhlenbeck‐process) together with the observationally equivalent structures. Furthermore it is shown that aliasing can even change the analytical properties of the time paths of the system: whereas the first component of the Ornstein‐Uhlenbeck‐process is differentiable, the trajectories of the aliasing structures are continuous, but not differentiable any more
Algorithm · Aliasing · Differentiable function · Identification (biology · Mathematical analysis · Mathematical optimization · Physics · Process (computing · Statistical physics · Stochastic differential equation · Applied Mathematics · Artificial Intelligence · Computer Science · Control Systems and Identification · Fault Detection and Control Systems · Mathematics · Target Tracking and Data Fusion in Sensor Networks
| Citations per year | 0.11 |
|---|---|
| Citation span | 1998 - 2018 (21) |
| Highly cited | No |