Forthcoming Articles

International Journal of Dynamical Systems and Differential Equations

International Journal of Dynamical Systems and Differential Equations (IJDSDE)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Dynamical Systems and Differential Equations (One paper in press)

Regular Issues

  • Related Technologies for Image Feature and Affective Computing Mapping via Psychological Cognition   Order a copy of this article
    by Jie Jiang 
    Abstract: Emotional computing has high computational costs, poor classification accuracy, lack of psychological theoretical support, and physiological signal acquisition is susceptible to noise interference. In response, this study proposes a deep learning based emotion recognition model that predicts a person's psychological state by using EEG signal data. This study preprocesses the proposed framework and extracts features from image data using discrete wavelet transform (DWT) and power spectral density (PSD). DWT extracts features as frequency bands, while PSD exports statistical features and parameters. Afterwards, this study retrieves spatial (channel) and temporal (brain peak and related latency) features from EEG data, and uses a 3D convolutional neural network for emotion classification to evaluate the proposed model. Meanwhile, this study also employs both subject dependent and subject independent procedures. The results indicate that extracting multidimensional complementary features in both frequency and spatial domains can improve recognition ability.
    Keywords: Affective computing; Psychological cognition; Emotional recognition; Convolutional Neural Network; Image Features; Deep Learning; Electroencephalogram Data.
    DOI: 10.1504/IJDSDE.2026.10076011
     

 

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