Skip to main content

Advertisement

Novel discrete initial-boosted Tabu learning neuron: dynamical analysis, DSP implementation, and batch medical image encryption

  • Published:
Applied Intelligence Aims and scope Submit manuscript

Abstract

A new discrete initial-boosted Tabu learning single neuron (DITLSN) is constructed using a new activation function to combine the Tabu learning neuron model in this paper. The complex and abundant dynamical behavior of the DITLSN is analyzed using bifurcation diagrams (BD) and Lyapunov exponential spectra(LEs), such as period, chaos, hyper-chaos, and attractor coexistence. In particular, the coexistence of initial-boosted hyperchaotic attractors found in numerical simulations of the DITLSN suggests that different initial states produce multiple highly complex attractors whose positions can change. The existence of attractor coexistence phenomenon makes chaotic parameters more difficult to be attacked by existing parameter identification algorithms, while its own high sensitivity to the initial state is more suitable for application scenarios such as secure communication. The results of the circuit implementation in the DSP platform are also in excellent agreement with the software simulation results. Finally, a batch medical image encryption scheme (BEIES) suitable for large-scale medical image encryption is designed. The performance analysis demonstrates that the designed scheme excels in the aspects of key performance, anti-statistical attack, anti-differential attack, robustness, etc., and most importantly, it has very high encryption and decryption efficiency, which is suitable for the application scenario of large-scale medical image batch processing.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Data Availability and Access

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Bao H, Ding R, Chen B, Xu Q, Bao B (2023) Two-dimensional non-autonomous neuron model with parameter-controlled multi-scroll chaotic attractors. Chaos, Solitons Fractals 169:113228

  2. Yang F, Ma J (2023) A controllable photosensitive neuron model and its application. Opt Laser Technol 163:109335

  3. Mou J, Ma T, Banerjee S, Zhang Y (2024) A novel memcapacitive-synapse neuron: bionic modeling, complex dynamics analysis and circuit implementation. Regular Papers, IEEE Transactions on Circuits and Systems I

    MATH  Google Scholar 

  4. Rbihou S, Joudar N-E, En-Naimani Z, Haddouch K (2023) Using crank-nicolson scheme for continuous hopfield network equilibrium, 201–210. Springer

    MATH  Google Scholar 

  5. Yu F, Shen H, Yu Q, Kong X, Sharma PK, Cai S (2022) Privacy protection of medical data based on multi-scroll memristive hopfield neural network. IEEE Trans Netw Sci Eng 10(2):845–858

    Article  MATH  Google Scholar 

  6. Deng Q, Wang C, Lin H (2024) Chaotic dynamical system of hopfield neural network influenced by neuron activation threshold and its image encryption. Nonlinear Dyn 1–18

  7. Doubla Isaac S, Njitacke ZT, Kengne J (2020) Effects of low and high neuron activation gradients on the dynamics of a simple 3d hopfield neural network. Int J Bifurcation Chaos 30(11):2050159

    Article  MathSciNet  MATH  Google Scholar 

  8. Doubla IS, Njitacke ZT, Ekonde S, Tsafack N, Nkapkop JDD, Kengne J (2021) Multistability and circuit implementation of tabu learning two-neuron model: application to secure biomedical images in iomt. Neural Comput & Applic 33:14945–14973

    Article  MATH  Google Scholar 

  9. Bao B, Hou L, Zhu Y, Wu H, Chen M (2020) Bifurcation analysis and circuit implementation for a tabu learning neuron model. AEU Int J Electron Commun 121:153235

  10. Wang Z, Bao H, Wu H, Chen M, Bao B (2023) Complex dynamics in a discrete adaptive synapse-based neuron model. Eur Phys J Plus 138(6):545

    Article  MATH  Google Scholar 

  11. Xu Q, Chen X, Chen B, Wu H, Li Z, Bao H (2023) Dynamical analysis of an improved fitzhugh-nagumo neuron model with multiplier-free implementation. Nonlinear Dyn 111(9):8737–8749

    Article  MATH  Google Scholar 

  12. Aslam MS, Radhika T, Chandrasekar A, Zhu Q (2024) Improved event-triggered-based output tracking for a class of delayed networked t–s fuzzy systems. Int J Fuzzy Syst 1–14

  13. Mou J, Zhang Z, Banerjee S, Zhang Y (2024) Combining semi-tensor product compressed sensing and session keys for low-cost encryption of batch information in wbans. IEEE Internet of Things Journal

  14. Peng Y, He S, Sun K (2022) Parameter identification for discrete memristive chaotic map using adaptive differential evolution algorithm. Nonlinear Dyn 107(1):1263–1275

    Article  MATH  Google Scholar 

  15. Zhou N-R, Tong L-J, Zou W-P (2023) Multi-image encryption scheme with quaternion discrete fractional tchebyshev moment transform and cross-coupling operation. Signal Process 211:109107

  16. He S, Zhan D, Wang H, Sun K, Peng Y (2022) Discrete memristor and discrete memristive systems. Entropy 24(6):786

    Article  MathSciNet  MATH  Google Scholar 

  17. Ma T, Mou J, Banerjee S, Cao Y (2023) Analysis of the functional behavior of fractional-order discrete neuron under electromagnetic radiation. Chaos, Solitons Fractals 176:114113

  18. Bao B, Wang Z, Hua Z, Chen M, Bao H (2023) Regime transition and multi-scroll hyperchaos in a discrete neuron model. Nonlinear Dyn 111(14):13499–13512

    Article  MATH  Google Scholar 

  19. Radhika T, Chandrasekar A, Vijayakumar V, Zhu Q (2023) Analysis of markovian jump stochastic cohen–grossberg bam neural networks with time delays for exponential input-to-state stability. Neural Process Lett 55(8):11055–11072

    Article  MATH  Google Scholar 

  20. Ren L, Qin L, Jahanshahi H, Mou J (2023) Infinitely many coexisting attractors and scrolls in a fractional-order discrete neuron map. Int J Bifurcation Chaos 33(16):2350197

    Article  MathSciNet  MATH  Google Scholar 

  21. Ding D, Chen X, Yang Z, Hu Y, Wang M, Niu Y (2023) Dynamics of stimuli-based fractional-order memristor-coupled tabu learning two-neuron model and its engineering applications. Nonlinear Dyn 111(2):1791–1817

    Article  MATH  Google Scholar 

  22. Lai Q, Hu G, Erkan U, Toktas A (2023) High-efficiency medical image encryption method based on 2d logistic-gaussian hyperchaotic map. Appl Math Comput 442:127738

  23. Peng Y, Lan Z, Li W, Li Y, Peng J (2022) Modeling different discrete memristive sine maps and its parameter identification. Eur Phys J Spec Top 231(16):3187–3196

    Article  MATH  Google Scholar 

  24. Zhang Z, Mou J, Banerjee S, Cao Y (2024) A chaotic hierarchical encryption/watermark embedding scheme for multi-medical images based on row–column confusion and closed-loop bi-directional diffusion. Chin Phys B 33(2):020503

  25. Chai X, Fu J, Gan Z, Lu Y, Zhang Y, Han D (2022) Exploiting semi-tensor product compressed sensing and hybrid cloud for secure medical image transmission. IEEE Int Things J 10(8):7380–7392

    Article  Google Scholar 

  26. Abdelfatah RI, Saqr HM, Nasr ME (2023) An efficient medical image encryption scheme for (wban) based on adaptive dna and modern multi chaotic map. Multimed Tools Appl 82(14):22213–22227

    Article  Google Scholar 

  27. Kamal ST, Hosny KM, Elgindy TM, Darwish MM, Fouda MM (2021) A new image encryption algorithm for grey and color medical images. Ieee Access 9:37855–37865

    Article  MATH  Google Scholar 

  28. Chen J, Sun S, Zhang L-b, Yang B, Wang W (2021) Compressed sensing framework for heart sound acquisition in internet of medical things. IEEE Trans Ind Inform 18(3):2000–2009

    Article  MATH  Google Scholar 

  29. Wu Y, Zhang L, Berretti S, Wan S (2022) Medical image encryption by content-aware dna computing for secure healthcare. IEEE Trans Ind Inform 19(2):2089–2098

    Article  MATH  Google Scholar 

  30. Cao H, Wang Y, Banerjee S, Cao Y, Mou J (2024) A discrete chialvo–rulkov neuron network coupled with a novel memristor model: design, dynamical analysis, dsp implementation and its application. Chaos, Solitons Fractals 179:114466

  31. Lai Q, Lai C, Zhang H, Li C (2022) Hidden coexisting hyperchaos of new memristive neuron model and its application in image encryption. Chaos, Solitons Fractals 158:112017

  32. Lin H, Wang C, Cui L, Sun Y, Xu C, Yu F (2022) Brain-like initial-boosted hyperchaos and application in biomedical image encryption. IEEE Trans Ind Inform 18(12):8839–8850

    Article  MATH  Google Scholar 

  33. Njitacke ZT, Nkapkop JDD, Signing VF, Tsafack N, Sone ME, Awrejcewicz J (2022) Novel extreme multistable tabu learning neuron: circuit implementation and application to cryptography. IEEE Transactions on Industrial Informatics

  34. Ding Y, Tan F, Qin Z, Cao M, Choo K-KR, Qin Z (2021) Deepkeygen: a deep learning-based stream cipher generator for medical image encryption and decryption. IEEE Trans Neural Netw Learn Syst 33(9):4915–4929

    Article  MATH  Google Scholar 

  35. Yu F, Shen H, Yu Q, Kong X, Sharma PK, Cai S (2022) Privacy protection of medical data based on multi-scroll memristive hopfield neural network. IEEE Trans Netw Sci Eng 10(2):845–858

    Article  MATH  Google Scholar 

  36. Wu Y, Zhang L, Berretti S, Wan S (2022) Medical image encryption by content-aware dna computing for secure healthcare. IEEE Trans Ind Inform 19(2):2089–2098

    Article  MATH  Google Scholar 

  37. Yu F, Shen H, Yu Q, Kong X, Sharma PK, Cai S (2022) Privacy protection of medical data based on multi-scroll memristive hopfield neural network. IEEE Trans Netw Sci Eng 10(2):845–858

    Article  MATH  Google Scholar 

  38. Gao X, Mou J, Banerjee S, Zhang Y (2023) Color-gray multi-image hybrid compression–encryption scheme based on bp neural network and knight tour. IEEE Transactions on Cybernetics

  39. Yu F, Xu S, Xiao X, Yao W, Huang Y, Cai S, Yin B, Li Y (2023) Dynamics analysis, fpga realization and image encryption application of a 5d memristive exponential hyperchaotic system. Integration 90:58–70

    Article  MATH  Google Scholar 

  40. Zhang Z, Cao Y, Jahanshahi H, Mou J (2023) Chaotic color multi-image compression-encryption/lsb data type steganography scheme for nft transaction security. J King Saud Univ Comput Inf Sci 35(10):101839

    MATH  Google Scholar 

  41. Tamil Thendral M, Ganesh Babu TR, Chandrasekar A, Cao Y (2022) Synchronization of markovian jump neural networks for sampled data control systems with additive delay components: analysis of image encryption technique. Mathematical methods in the applied sciences

  42. Sha Y, Mou J, Banerjee S, Zhang Y (2023) Exploiting flexible and secure cryptographic technique for multi-dimensional image based on graph data structure and three-input majority gate. IEEE Transactions on Industrial Informatics

  43. Zhou N-R, Tong L-J, Zou W-P (2023) Multi-image encryption scheme with quaternion discrete fractional tchebyshev moment transform and cross-coupling operation. Signal Proc 211:109107

  44. Hua Z, Zhang K, Li Y, Zhou Y (2021) Visually secure image encryption using adaptive-thresholding sparsification and parallel compressive sensing. Signal Proc 183:107998

  45. Sun X, Shao Z, Shang Y, Liang M, Yang F (2021) Multiple-image encryption based on cascaded gyrator transforms and high-dimensional chaotic system. Multimed Tools Appl 80(10):15825–15848

  46. Zhang Z, Mou J, Zhou N, Banerjee S, Cao Y (2024) Multi-cube encryption scheme for multi-type images based on modified klotski game and hyperchaotic map. Nonlinear Dyn 1–21

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos.62061014); Technological innovation projects in the field of artificial intelligence in Liaoning province(Grant Nos.2023JH26 /10300011); Basic scientific research projects in department of education of Liaoning Province(Grant Nos.JYTZD2023021).

Author information

Authors and Affiliations

Authors

Contributions

Zheyi Zhang designed and carried out experiments, data analyzed and manuscript wrote. Nanrun Zhou, Yinghong Cao, and Yushu Zhang made the theoretical guidance for this paper. Jun Mou carried out experiment and improved the algorithm. All authors reviewed the manuscript.

Corresponding authors

Correspondence to Yinghong Cao or Jun Mou.

Ethics declarations

Competing Interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Ethical and Informed Consent for Data Used

The test images used in this paper are from the MedPix image database (https://medpix.nlm.nih.gov/home) and are used for scientific research only, not for other purposes, and without copyright disputes.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Z., Cao, Y., Zhou, N. et al. Novel discrete initial-boosted Tabu learning neuron: dynamical analysis, DSP implementation, and batch medical image encryption. Appl Intell 55, 61 (2025). https://doi.org/10.1007/s10489-024-05918-9

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10489-024-05918-9

Keywords