dorsal/arxiv
View SchemaRecognizing different types of stochastic processes
| Authors | Jong U. Kim, Laszlo B. Kish |
|---|---|
| Categories | |
| ArXiv ID | physics/0510118 |
| URL | https://arxiv.org/abs/physics/0510118 |
Abstract
We propose a new cross-correlation method that can recognize independent realizations of the same type of stochastic processes and can be used as a new kind of pattern recognition tool in biometrics, sensing, forensic, security and image processing applications. The method, which we call bispectrum correlation coefficient method, makes use of the cross-correlation of the bispectra. Three kinds of cross-correlation coefficients are introduced. To demonstrate the new method, six different random telegraph signals are tested, where four of them have the same power density spectrum. It is shown that the three coefficients can map the different stochastic processes to specific sub-volumes in a cube.
{
"annotation_id": "f52bb9fd-562f-4fc8-947f-5e5ef435786b",
"date_created": "2026-03-02T18:01:03.873000Z",
"date_modified": "2026-03-02T18:01:03.873000Z",
"file_hash": "e453fdd7511416890af2deb358cf658c73d07f2ec9624d445ed64acd76df1d1b",
"private": false,
"record": {
"abstract": "We propose a new cross-correlation method that can recognize independent\nrealizations of the same type of stochastic processes and can be used as a new\nkind of pattern recognition tool in biometrics, sensing, forensic, security and\nimage processing applications. The method, which we call bispectrum correlation\ncoefficient method, makes use of the cross-correlation of the bispectra. Three\nkinds of cross-correlation coefficients are introduced. To demonstrate the new\nmethod, six different random telegraph signals are tested, where four of them\nhave the same power density spectrum. It is shown that the three coefficients\ncan map the different stochastic processes to specific sub-volumes in a cube.",
"arxiv_id": "physics/0510118",
"authors": [
"Jong U. Kim",
"Laszlo B. Kish"
],
"categories": [
"physics.data-an"
],
"title": "Recognizing different types of stochastic processes",
"url": "https://arxiv.org/abs/physics/0510118"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "7cb998c8-58c0-4a8a-8f3a-1e683c54f0dc",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}