Jove
Visualize
Contact Us

Related Concept Videos

State Space Representation01:27

State Space Representation

625
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
625
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

1.6K
Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...
1.6K
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

398
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
398
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

290
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
290
IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

1.9K
Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single...
1.9K
IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration01:16

IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration

3.1K
A covalently bonded heteronuclear diatomic molecule can be modeled as two vibrating masses connected by a spring. The vibrational frequency of the bond can be expressed using an equation derived from Hooke's law, which describes how the force applied to stretch or compress a spring is proportional to the displacement of the spring. In this case, the atoms behave like masses, and the bond acts like a spring.
According to Hooke's law, the vibrational frequency is directly proportional to...
3.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Accurate and robust real-time prediction of September Arctic sea ice.

Chaos (Woodbury, N.Y.)·2026
Same author

Noise-driven topological changes in chaotic dynamics.

Chaos (Woodbury, N.Y.)·2021
Same author

Reduced-order models for coupled dynamical systems: Data-driven methods and the Koopman operator.

Chaos (Woodbury, N.Y.)·2021
Same author

Efficient reduction for diagnosing Hopf bifurcation in delay differential systems: Applications to cloud-rain models.

Chaos (Woodbury, N.Y.)·2020
Same author

Publisher's Note: Comment on "Nonparametric forecasting of low-dimensional dynamical systems" [Phys. Rev. E 93, 036201 (2016)].

Physical review. E·2016
Same author

Comment on "Nonparametric forecasting of low-dimensional dynamical systems ".

Physical review. E·2016
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Feb 22, 2026

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
07:11

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

3.0K

Data-adaptive harmonic spectra and multilayer Stuart-Landau models.

Mickaël D Chekroun1, Dmitri Kondrashov1

  • 1Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, California 90095-1565, USA.

Chaos (Woodbury, N.Y.)
|October 2, 2017
PubMed
Summary

This study introduces data-adaptive harmonic (DAH) decomposition for analyzing multivariate time series. DAH modes reveal key dynamics and enable efficient modeling using multilayer stochastic models.

More Related Videos

Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research
08:12

Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research

Published on: February 16, 2024

16.0K
Author Spotlight: Unveiling the Potential of VSFG Microscopy in Studying Mesoscopically Heterogeneous Self-Assembled Structures
08:49

Author Spotlight: Unveiling the Potential of VSFG Microscopy in Studying Mesoscopically Heterogeneous Self-Assembled Structures

Published on: December 1, 2023

2.1K

Related Experiment Videos

Last Updated: Feb 22, 2026

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
07:11

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

3.0K
Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research
08:12

Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research

Published on: February 16, 2024

16.0K
Author Spotlight: Unveiling the Potential of VSFG Microscopy in Studying Mesoscopically Heterogeneous Self-Assembled Structures
08:49

Author Spotlight: Unveiling the Potential of VSFG Microscopy in Studying Mesoscopically Heterogeneous Self-Assembled Structures

Published on: December 1, 2023

2.1K

Area of Science:

  • Dynamical systems analysis
  • Time series decomposition
  • Spectral analysis

Background:

  • Multivariate time series analysis often requires complex models.
  • Extracting meaningful dynamics from complex data remains challenging.
  • Existing methods may not fully capture data-adaptive features.

Purpose of the Study:

  • To develop a novel harmonic decomposition method for multivariate time series.
  • To introduce data-adaptive harmonic (DAH) modes and associated spectra.
  • To demonstrate the effectiveness of DAH decomposition in modeling complex systems.

Main Methods:

  • Integral operator approach with periodic semigroup kernels.
  • Derivation of spectral decomposition theorems for mixing invariant measures.
  • Definition of multidimensional power and phase spectra based on data-adaptive eigenmodes.
  • Application of DAH decomposition to multilayer stochastic models (MSMs).

Main Results:

  • Eigenvalues correspond to singular values of cross-spectral matrices, grouped by Fourier frequency.
  • DAH modes exhibit data-adaptive phases, enabling multidimensional phase spectrum definition.
  • DAH decomposition simplifies modeling to frequency-stacked elemental models.
  • Successful application to Lorenz 96 and stochastic heat equation models.

Conclusions:

  • DAH decomposition effectively extracts spatio-temporal modes and reveals dynamical features.
  • Multilayer Stuart-Landau models (MSLMs) accurately capture time-evolving field patterns and statistics.
  • The DAH framework offers a powerful tool for analyzing and modeling complex time series data.