0.65 V integrable electronic realisation of integer- and fractional-order Hindmarsh–Rose neuron model using companding technique

作者: Farooq Ahmad Khanday , Mohammad Rafiq Dar , Nasir Ali Kant , Josep L. Rossello , Costas Psychalinos

DOI: 10.1049/IET-CDS.2018.5033

关键词: IntegratorCompandingCapacitorElectronic circuitTopologyTransistorComputer scienceDifferentiatorCMOSBiological neuron model

摘要: Some neurons like neocortical pyramidal adapt with multiple time-scales, which is consistent fractional-order differentiation. The neuron models are therefore believed to portray the firing rate of more accurately than their integer-order models. It has been studied that as fractional order differentiator and integrator involved in model decreases, bursting frequency increases. opposite effect observed on increasing external excitation. In this study, integer- Hindmarsh–Rose (HR) have implemented using sinh companding technique. Besides, application HR a simple network two also considered. designs offer low-voltage low-power implementation along electronic tunability performance characteristics. Due use only metal-oxide semiconductor (MOS) transistors grounded capacitors, proposed can be integrated chip form. On comparing existing implementations, show better terms power consumption, supply voltage, flexibility. circuits verified 130 nm complementary MOS (CMOS) technology process provided by Austrian Micro Systems HSPICE simulation software.

参考文章(38)
Mohsen Hayati, Moslem Nouri, Saeed Haghiri, Derek Abbott, Digital Multiplierless Realization of Two Coupled Biological Morris-Lecar Neuron Model IEEE Transactions on Circuits and Systems. ,vol. 62, pp. 1805- 1814 ,(2015) , 10.1109/TCSI.2015.2423794
Brian N Lundstrom, Matthew H Higgs, William J Spain, Adrienne L Fairhall, Fractional differentiation by neocortical pyramidal neurons. Nature Neuroscience. ,vol. 11, pp. 1335- 1342 ,(2008) , 10.1038/NN.2212
Weihua Deng, Changpin Li, Jinhu Lü, Stability analysis of linear fractional differential system with multiple time delays Nonlinear Dynamics. ,vol. 48, pp. 409- 416 ,(2007) , 10.1007/S11071-006-9094-0
S.R. Dtchetgnia Djeundam, R. Yamapi, G. Filatrella, T.C. Kofane, Stability of the synchronized network of Hindmarsh–Rose neuronal models with nearest and global couplings Communications in Nonlinear Science and Numerical Simulation. ,vol. 22, pp. 545- 563 ,(2015) , 10.1016/J.CNSNS.2014.08.003
P. Ahmadi, B. Maundy, A.S. Elwakil, L. Belostotski, High-quality factor asymmetric-slope band-pass filters: A fractional-order capacitor approach Iet Circuits Devices & Systems. ,vol. 6, pp. 187- 197 ,(2012) , 10.1049/IET-CDS.2011.0239
Wei Du-Qu, Luo Xiao-Shu, Coherence Resonance and Noise-Induced Synchronization in Hindmarsh–Rose Neural Network with Different Topologies Communications in Theoretical Physics. ,vol. 48, pp. 759- 762 ,(2007) , 10.1088/0253-6102/48/4/039
Ahmed Elwakil, Fractional-Order Circuits and Systems: An Emerging Interdisciplinary Research Area IEEE Circuits and Systems Magazine. ,vol. 10, pp. 40- 50 ,(2010) , 10.1109/MCAS.2010.938637
Dong Jun, Zhang Guang-jun, Xie Yong, Yao Hong, Wang Jue, Dynamic behavior analysis of fractional-order Hindmarsh–Rose neuronal model Cognitive Neurodynamics. ,vol. 8, pp. 167- 175 ,(2014) , 10.1007/S11571-013-9273-X
Hongjie Yu, Jianhua Peng, Chaotic synchronization and control in nonlinear-coupled Hindmarsh–Rose neural systems Chaos, Solitons & Fractals. ,vol. 29, pp. 342- 348 ,(2006) , 10.1016/J.CHAOS.2005.08.075