LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 2 of total 2

Search options

  1. Article: Optimization of fractional-order chaotic cellular neural networks by metaheuristics.

    Tlelo-Cuautle, Esteban / González-Zapata, Astrid Maritza / Díaz-Muñoz, Jonathan Daniel / de la Fraga, Luis Gerardo / Cruz-Vega, Israel

    The European physical journal. Special topics

    2022  Volume 231, Issue 10, Page(s) 2037–2043

    Abstract: Artificial neural networks have demonstrated to be very useful in solving problems in artificial intelligence. However, in most cases, ANNs are considered integer-order models, limiting the possible applications in recent engineering problems. In ... ...

    Abstract Artificial neural networks have demonstrated to be very useful in solving problems in artificial intelligence. However, in most cases, ANNs are considered integer-order models, limiting the possible applications in recent engineering problems. In addition, when dealing with fractional-order neural networks, almost any work shows cases when varying the fractional order. In this manner, we introduce the optimization of a fractional-order neural network by applying metaheuristics, namely: differential evolution (DE) and accelerated particle swarm optimization (APSO) algorithms. The case study is a chaotic cellular neural network (CNN), for which the main goal is generating fractional orders of the neurons whose Kaplan-Yorke dimension is being maximized. We propose a method based on Fourier transform to evaluate if the generated time series is chaotic or not. The solutions that do not have chaotic behavior are not passed to the time series analysis (TISEAN) software, thus saving execution time. We show the best solutions provided by DE and APSO of the attractors of the fractional-order chaotic CNNs.
    Language English
    Publishing date 2022-01-21
    Publishing country France
    Document type Journal Article
    ZDB-ID 2267176-6
    ISSN 1951-6401 ; 1951-6355
    ISSN (online) 1951-6401
    ISSN 1951-6355
    DOI 10.1140/epjs/s11734-022-00452-6
    Database MEDical Literature Analysis and Retrieval System OnLINE

    Full text online

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  2. Article ; Online: Chaotic Image Encryption Using Hopfield and Hindmarsh-Rose Neurons Implemented on FPGA.

    Tlelo-Cuautle, Esteban / Díaz-Muñoz, Jonathan Daniel / González-Zapata, Astrid Maritza / Li, Rui / León-Salas, Walter Daniel / Fernández, Francisco V / Guillén-Fernández, Omar / Cruz-Vega, Israel

    Sensors (Basel, Switzerland)

    2020  Volume 20, Issue 5

    Abstract: Chaotic systems implemented by artificial neural networks are good candidates for data encryption. In this manner, this paper introduces the cryptographic application of the Hopfield and the Hindmarsh-Rose neurons. The contribution is focused on finding ... ...

    Abstract Chaotic systems implemented by artificial neural networks are good candidates for data encryption. In this manner, this paper introduces the cryptographic application of the Hopfield and the Hindmarsh-Rose neurons. The contribution is focused on finding suitable coefficient values of the neurons to generate robust random binary sequences that can be used in image encryption. This task is performed by evaluating the bifurcation diagrams from which one chooses appropriate coefficient values of the mathematical models that produce high positive Lyapunov exponent and Kaplan-Yorke dimension values, which are computed using TISEAN. The randomness of both the Hopfield and the Hindmarsh-Rose neurons is evaluated from chaotic time series data by performing National Institute of Standard and Technology (NIST) tests. The implementation of both neurons is done using field-programmable gate arrays whose architectures are used to develop an encryption system for RGB images. The success of the encryption system is confirmed by performing correlation, histogram, variance, entropy, and Number of Pixel Change Rate (NPCR) tests.
    Language English
    Publishing date 2020-02-28
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s20051326
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

To top