Nonlinear spiking neural P systemsTime series classificationReservoir computing (RC) is a novel class of recurrent neural networks (RNN) models. Nonlinear spiking neural P (NSNP) systems are neural-like computing models with nonlinear spiking mechanisms. By introducing NSNP systems as the reservoir, ...
This paper proposes NSNPRIS (convolutional nonlinear spiking neural P systems for referring image segmentation), a novel model based on convolutional nonlinear spiking neural P systems. NSNPRIS features NSNPFusion and Language Gate modules to enhance feature interaction during encoding, along with an ...
Efficient coding is often considered a natural assumption for sensory systems because of the need to preserve energy associated with neuronal activity58. However, whether the retinal output is energy-efficient in vivo has been debated59. Moreover, feature detection might have different requirements than...
Bao, H., Chen, Z., Cai, J., et al.: Memristive cyclic three-neuron-based neural network with chaos and global coexisting attractors. Sci. China Technol. Sci. 65, 2582–2592 (2022) ADS MATH Google Scholar Podlubny, I.: Fractional-order systems and \(\text{ PI}^{\lambda }\)\(\...
Large-scale neural recording with single-neuron resolution has revealed the functional complexity of the neural systems. However, even under well-designed task conditions, the cortex-wide network exhibits highly dynamic trial variability, posing challenges to the conventional trial-averaged analysis. To ...
Some nonlinear systems possess innate capabilities of enhancing weak signal transmissions through a unique process called Stochastic Resonance (SR). However, existing SR mechanism suffers limited signal enhancement from inappropriate entraining signals.
The main aspects of nonlinear systems that have utility in neurobiology are these: first, the understanding that from a single measured quantity, such as membrane voltage, one can reconstruct a proxy state space which describes the degrees of freedom active in the observed neural circuit; second,...
NonlinearAnalysis:HybridSystems journalhomepage:.elsevier/locate/nahs Multistability,bifurcations,andbiologicalneuralnetworks:Asynaptic drivefiringmodelforcerebralcortextransitionintheinductionof generalanesthesia QingHui a ,WassimM.Haddad b,∗ ,JamesM.Bailey c a DepartmentofMechanicalEngineering,TexasTechUniversity...
Liu, Z.L., Han, F., Wang, Q.Y.: A review of computational models for gamma oscillation dynamics: from spiking neurons to neural masses. Nonlinear Dyn. 108(3), 1849–1866 (2022) Google Scholar Bao, H., Chen, Z.G., Cai, J.M., et al.: Memristive cyclic three-neuron-based neu...
Koopman operators linearize nonlinear dynamical systems, making their spectral information of crucial interest. Numerous algorithms have been developed to