Dynamic Behavior of Artificial Hodgkin–Huxley Neuron Model Subject to Additive Noise

2016 ◽  
Vol 46 (9) ◽  
pp. 2083-2093 ◽  
Author(s):  
Qi Kang ◽  
BingYao Huang ◽  
MengChu Zhou
Keyword(s):  
Dynamic Behavior ◽  
Neuron Model ◽  
Additive Noise ◽  
Model Subject

Simplified analysis of a stochastic system

1979 ◽  
Vol 44 (2) ◽  
pp. 328-339
Author(s):  
Vladimír Herles
Keyword(s):  
Statistical Analysis ◽  
Dynamic Behavior ◽  
Stochastic System ◽  
Additive Noise ◽  
Random Parameter ◽  
Systematic Difference ◽  
Order System ◽  
Constant Parameter ◽  
Random Parameters ◽  
Simplified Analysis

Contradictious results published by different authors about the dynamics of systems with random parameters have been examined. Statistical analysis of the simple 1st order system proves that the random parameter can cause a systematic difference in the dynamic behavior that cannot be (in general) described by the usual constant-parameter model with the additive noise at the output.

NOISE-ENHANCED TRANSMISSION OF TIME-MODULATED NEUROTRANSMITTER RANDOM POINT TRAINS IN A NOISY NEURON

2016 ◽  
Vol 24 (02n03) ◽  
pp. 367-383 ◽  
Author(s):  
TIANQUAN FENG ◽  
MING YI
Keyword(s):  
Neuron Model ◽  
Additive Noise ◽  
Average Rate ◽  
Random Point ◽  
Noise Power ◽  
Enhanced Transmission ◽  
Maximum Value ◽  
Optimal Value ◽  
Snr Gain ◽  
Noise Power Density

We numerically investigate the transmission of time-modulated random point trains in a conductance-based neuron model by including shot noise described as additive noise trains. The results show that additive noise trains can induce neuron responses exhibiting correlation with the temporally modulated random point trains. In addition, the additive noise power density can be increased up to an optimal value where the output signal-noise ratio (SNR) reaches a maximum value. This property of noise-enhanced transmission of random point trains can be related to the stochastic resonance (SR) phenomenon. More interestingly, we find that the SNR gain can exceed unity and can also be optimized by tuning the average rate of the input random point trains. The present study illustrates the potential to utilize the additive noise and temporally modulated random point trains for optimizing the response of the neuron to inputs, as well as a guidance in the design of information processing devices to random neuron spiking.

scholarly journals Modeling dynamic behavior of striatal medium spiny neurons with point neuron models

2018 ◽  
Vol 2018 (1) ◽  
Keyword(s):  
Dynamic Behavior ◽  
Calcium Current ◽  
Neuron Model ◽  
Dynamical Behavior ◽  
Medium Spiny Neuron ◽  
Computational Time ◽  
High Threshold ◽  
Neuron Models ◽  
Synaptic Currents ◽  
Cortical Inputs

The aim of this work is to investigate the role of network organization and the neuron model type on the collective dynamic behavior of striatal population. For that purpose, two different scale neuron models which are phenomenological Izhikevich and conductance-based Hodgkin-Huxley (HH) type are used to investigate the dynamic behavior of MS neurons. Two network architectures are proposed with inhibitory and excitatory synaptic currents. In these networks, while all MS neurons affect each other with inhibitory synaptic currents, an excitatory current is applied to all MS neurons in the first layer, to represent the cortical inputs. A mathematical model of a medium spiny neuron of striatum based on HH type neuron model is proposed using different calcium channels and its dynamical behavior is investigated. It is observed that when the original HH model is used, regular spiking type behavior is observed. Including the high threshold calcium current, after hyperpolarization calcium current and voltage gated potasium current into the model improves the modeling capabilities. With extended ion channels, in addition to regular spiking behavior, bursting with resting stage are obtained. Then, Izhikevich neuron model is used in the network structures to compare the dynamic behaviors and computational time.

Ball bearing turbocharger vibration management: application on high speed balancer

2020 ◽  
Vol 21 (6) ◽  
pp. 619
Author(s):  
Kostandin Gjika ◽  
Antoine Costeux ◽  
Gerry LaRue ◽  
John Wilson
Keyword(s):  
Dynamic Behavior ◽  
High Speed ◽  
Internal Combustion Engines ◽  
Ball Bearing ◽  
Squeeze Film ◽  
Design And Technology ◽  
Squeeze Film Damper ◽  
Damping Coefficients ◽  
Bearing Loads ◽  
Stiffness And Damping

Today's modern internal combustion engines are increasingly focused on downsizing, high fuel efficiency and low emissions, which requires appropriate design and technology of turbocharger bearing systems. Automotive turbochargers operate faster and with strong engine excitation; vibration management is becoming a challenge and manufacturers are increasingly focusing on the design of low vibration and high-performance balancing technology. This paper discusses the synchronous vibration management of the ball bearing cartridge turbocharger on high-speed balancer and it is a continuation of papers [1–3]. In a first step, the synchronous rotordynamics behavior is identified. A prediction code is developed to calculate the static and dynamic performance of “ball bearing cartridge-squeeze film damper”. The dynamic behavior of balls is modeled by a spring with stiffness calculated from Tedric Harris formulas and the damping is considered null. The squeeze film damper model is derived from the Osborne Reynolds equation for incompressible and synchronous fluid loading; the stiffness and damping coefficients are calculated assuming that the bearing is infinitely short, and the oil film pressure is modeled as a cavitated π film model. The stiffness and damping coefficients are integrated on a rotordynamics code and the bearing loads are calculated by converging with the bearing eccentricity ratio. In a second step, a finite element structural dynamics model is built for the system “turbocharger housing-high speed balancer fixture” and validated by experimental frequency response functions. In the last step, the rotating dynamic bearing loads on the squeeze film damper are coupled with transfer functions and the vibration on the housings is predicted. The vibration response under single and multi-plane unbalances correlates very well with test data from turbocharger unbalance masters. The prediction model allows a thorough understanding of ball bearing turbocharger vibration on a high speed balancer, thus optimizing the dynamic behavior of the “turbocharger-high speed balancer” structural system for better rotordynamics performance identification and selection of the appropriate balancing process at the development stage of the turbocharger.

Prediction of gear wear for the estimation of solar array drive dynamic behavior

2006 ◽  
Vol 12 (4) ◽  
pp. 33-37
Author(s):  
V.E. Shatikhin ◽  
◽  
L.P. Semenov ◽  
V.S. Khoroshylov ◽  
V.M. Popel' ◽  
...  
Keyword(s):  
Dynamic Behavior ◽  
Solar Array
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