Target wave in the network coupled by thermistors

Zhang, Xiufang; Yao, Zhao; Guo, Yeye

doi:10.1016/j.chaos.2020.110455

Cited by 19 publications

(2 citation statements)

References 82 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When functional components such as phototube [17,18], thermistor [19,20], Josephson junction [21][22][23] and memristor [24][25][26] are incorporated into the neural circuits [27][28][29][30][31], external physical signals including light, temperature changes, magnetic field can be estimated by imposing equivalent channel currents on the neuron models. Biological neurons show distinct self-adaptive property and inner parameter adjustment or synaptic controllability are crucial for selecting suitable firing modes in fast way.…”

Section: Introductionmentioning

confidence: 99%

Dynamics in a light-sensitive neuron with two capacitive variables

Wang,

Lv,

Zhang

et al. 2024

Phys. Scr.

View full text Add to dashboard Cite

Involvement of two capacitive variables into neuron models provides better description of the cell membrane property and then the diversity effect of electromagnetic field inner and outer of the cell membrane can be estimated in clear way. Specific electric components can be combined to build equivalent neural circuits for reproducing similar neural activities under some self-adaptive control schemes. A phototube converts external light into electric stimuli and the injected energy is encoded to excite the cell membranes for presenting suitable firing patterns. Two capacitors are connected via a linear resistor for mimicking the energy exchange and changes of membrane potentials. Combination of memristor into an additive branch circuit of the neural circuit can estimate the effect of electromagnetic induction and energy absorption. The energy function H for this light-sensitive and memristive neuron is calculated in theoretical way, and the average energy function <H> can predict the occurrence of stochastic resonance, which can be confirmed by estimating the distribution of signal to noise ratios. The firing mode is relative to the energy value of the neuron, and a control law is suggested to control the mode transition in neural activities in an adaptive way.

show abstract

Section: Introductionmentioning

confidence: 99%

Dynamics in a light-sensitive neuron with two capacitive variables

Wang,

Lv,

Zhang

et al. 2024

Phys. Scr.

View full text Add to dashboard Cite

show abstract

“…Laser beams, when introduced to a highly nonlocal medium, undergo a transformation, exhibiting a series of novel and captivating dynamic characteristics. These characteristics, ranging from beam shaping to propagation dynamics, have been meticulously studied, leading to several groundbreaking discoveries [18,19,20,21,22,23]. Nonlocal media can be equivalent to some potential wells, so the dynamic characteristics of beam propagation in highly nonlocal media can also be extended to these potential wells [24,25,26].…”

Section: Introductionmentioning

confidence: 99%

Cosine-Gaussian breathers controlled by the initial conditions in highly nonlocal media

Pan,

Xu,

Dai

2024

Opt Quant Electron

View full text Add to dashboard Cite

The study delves into the behavior of cos-Gaussian breathers navigating through a highly nonlocal medium, with a spotlight on their width and intensity variations under different parameter adjustments. The mathematical formulas describing the characteristics of cos-Gaussian beam have been derived. By controlling the parameters, the transverse width of cos-Gaussian beams can exhibit various variations, reflecting various mode transformations. We scrutinized how alterations in cosine parameters, offset distance, and initial energy manifest in the breather's width and shape during propagation. Our observations underscore the significant influence of these parameters on the dynamic evolution and morphology of cos-Gaussian breathers, thereby unveiling the potential application of using parameters to control the dynamic characteristics of cos-Gaussian beam transmission.

show abstract

The effects of temperature on the dynamics of the biological neural network

Jabbari

Karamati

2022

J Biol Phys

View full text Add to dashboard Cite

Target wave in the network coupled by thermistors

Cited by 19 publications

References 82 publications

Dynamics in a light-sensitive neuron with two capacitive variables

Dynamics in a light-sensitive neuron with two capacitive variables

Cosine-Gaussian breathers controlled by the initial conditions in highly nonlocal media

The effects of temperature on the dynamics of the biological neural network

Contact Info

Product

Resources

About