Saved in:
Bibliographic Details
Main Authors: Singh, Mairembam Kelvin, Sharma, A. Surjalal, Singh, N. Nimai, Singh, Moirangthem Shubhakanta
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2403.06987
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866911793355423744
author Singh, Mairembam Kelvin
Sharma, A. Surjalal
Singh, N. Nimai
Singh, Moirangthem Shubhakanta
author_facet Singh, Mairembam Kelvin
Sharma, A. Surjalal
Singh, N. Nimai
Singh, Moirangthem Shubhakanta
contents Complexity is often exhibited in dynamical systems, where certain parameters evolve with time in a strange and chaotic nature. These systems lack predictability and are common in the physical world. Dissipative systems are one of such systems where the volume of the phase space contracts with time. On the other hand, we employ dimensionality reduction techniques to study complicated and complex data, which are tough to analyse. The Principal Component Analysis (PCA) is a dimensionality reduction technique used as a means to study complex data. Through PCA, we studied the reduced dimensional features of the numerical data generated by a nonlinear partial differential equation called the Korteweg de Vries (KdV) equation, which is a nonlinear dispersive system, where solitary waves travel along a specific direction with finite amplitude. Dissipative nature, specific to that of the Lorenz system, were observed in the dimensionally reduced data, which implies a transition from a dispersive system to a dissipative system.
format Preprint
id arxiv_https___arxiv_org_abs_2403_06987
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Data driven approach to study the transition from dispersive to dissipative systems through dimensionality reduction techniques
Singh, Mairembam Kelvin
Sharma, A. Surjalal
Singh, N. Nimai
Singh, Moirangthem Shubhakanta
Dynamical Systems
Complexity is often exhibited in dynamical systems, where certain parameters evolve with time in a strange and chaotic nature. These systems lack predictability and are common in the physical world. Dissipative systems are one of such systems where the volume of the phase space contracts with time. On the other hand, we employ dimensionality reduction techniques to study complicated and complex data, which are tough to analyse. The Principal Component Analysis (PCA) is a dimensionality reduction technique used as a means to study complex data. Through PCA, we studied the reduced dimensional features of the numerical data generated by a nonlinear partial differential equation called the Korteweg de Vries (KdV) equation, which is a nonlinear dispersive system, where solitary waves travel along a specific direction with finite amplitude. Dissipative nature, specific to that of the Lorenz system, were observed in the dimensionally reduced data, which implies a transition from a dispersive system to a dissipative system.
title Data driven approach to study the transition from dispersive to dissipative systems through dimensionality reduction techniques
topic Dynamical Systems
url https://arxiv.org/abs/2403.06987