Jove
Visualize
Contact Us
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 Concept Videos

Signal Flow Graphs01:18

Signal Flow Graphs

217
Signal-flow graphs offer a streamlined and intuitive approach to representing control systems, providing an alternative to traditional block diagrams. These graphs use branches to symbolize systems and nodes to represent signals, effectively illustrating the relationships and interactions within the system.
In a signal-flow graph, branches denote the system's transfer functions, while nodes represent the signals. The direction of signal flow is indicated by arrows, with the corresponding...
217

You might also read

Related Articles

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

Sort by
Same author

Modeling remote healthcare adoption with fractional-order reaction-diffusion: stability and policy insights.

Theory in biosciences = Theorie in den Biowissenschaften·2026
Same author

Locally active memristor-based Chialvo neuron model: bifurcation, multistability, and noise effects.

Cognitive neurodynamics·2026
Same author

Hilbert matrix-based weight initialization enhanced by mutual information for neural network optimization.

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

Corrigendum to "Non-similar solution development for entropy optimized flow of Jeffrey liquid" [Heliyon Volume 9, Issue 8, August 2023, Article e18603].

Heliyon·2025
Same author

Global, Regional, and National Burden of Nontraumatic Subarachnoid Hemorrhage: The Global Burden of Disease Study 2021.

JAMA neurology·2025
Same author

A novel chaotic system with one absolute term: stability, ultimate boundedness, and image encryption.

Heliyon·2025

Related Experiment Video

Updated: Jun 29, 2025

A Method for Growing Bio-memristors from Slime Mold
07:46

A Method for Growing Bio-memristors from Slime Mold

Published on: November 2, 2017

8.9K

Assessing sigmoidal function on memristive maps.

Vo Phu Thoai1, Viet-Thanh Pham1, Giuseppe Grassi2

  • 1Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Viet Nam.

Heliyon
|March 25, 2024
PubMed
Summary

This study introduces novel 2D and 3D discrete maps by integrating memristors and sigmoidal functions, enhancing complex dynamics research. The new STMM1 map demonstrates feasibility and altered dynamics, paving the way for advanced applications.

Keywords:
ChaosDynamicsNonlinearSymmetry

More Related Videos

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
08:07

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

7.8K
Introduction to Solid Supported Membrane Based Electrophysiology
19:56

Introduction to Solid Supported Membrane Based Electrophysiology

Published on: May 11, 2013

15.2K

Related Experiment Videos

Last Updated: Jun 29, 2025

A Method for Growing Bio-memristors from Slime Mold
07:46

A Method for Growing Bio-memristors from Slime Mold

Published on: November 2, 2017

8.9K
Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
08:07

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

7.8K
Introduction to Solid Supported Membrane Based Electrophysiology
19:56

Introduction to Solid Supported Membrane Based Electrophysiology

Published on: May 11, 2013

15.2K

Area of Science:

  • Complex Dynamics
  • Nonlinear Systems
  • Applied Mathematics

Background:

  • Memristors are key components for discrete map construction, vital for complex dynamics.
  • Existing mapping techniques can be enhanced through novel integrations.
  • Sigmoidal functions offer unique properties for modifying map behavior.

Purpose of the Study:

  • To propose innovative 2D and 3D mapping techniques by integrating memristors and sigmoidal functions.
  • To investigate the dynamics and feasibility of a novel memristive sigmoidal chaotic map (STMM1).
  • To explore the impact of sigmoidal functions on map properties like fixed points and symmetry.

Main Methods:

  • Integration of memristive devices with sigmoidal functions to create new discrete maps.
  • Analysis of the dynamical properties of the proposed maps, including the STMM1 map.
  • Examination of the effects of multiple sigmoidal functions and memristors on chaotic map behavior.

Main Results:

  • The amalgamation of memristors and sigmoidal functions is confirmed as a viable approach for generating 2D and 3D maps.
  • Chaotic maps incorporating multiple sigmoidal functions and memristors exhibit particularly interesting dynamics.
  • The novel STMM1 map shows promising dynamics and feasibility for practical applications.
  • Sigmoidal functions were found to alter the number of fixed points and the symmetry of the maps.

Conclusions:

  • The integration of memristors and sigmoidal functions offers a powerful strategy for developing advanced discrete maps.
  • The proposed STMM1 map represents a significant contribution to the field of chaotic dynamics.
  • These findings open new avenues for the application of memristive-based maps in various scientific and engineering domains.