Synchronization and FPGA realization of fractional-order Izhikevich neuron model

Mohammed F. Tolba; Abdulaziz H. Elsafty; Mina Armanyos; Lobna A. Said; Ahmed H. Madian; Ahmed G. Radwan

doi:10.1016/j.mejo.2019.05.003

Synchronization and FPGA realization of fractional-order Izhikevich neuron model

Mohammed F. Tolba, Abdulaziz H. Elsafty, Mina Armanyos, Lobna A. Said, Ahmed H. Madian, Ahmed G. Radwan

Research output: Contribution to journal › Article › peer-review

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Abstract

This paper generalizes the Izhikevich neuron model in the fractional-order domain for better modeling of neuron dynamics. Accurate and computationally efficient numerical techniques such as non-standard finite difference (NSFD) scheme is used to solve the neuron system in the fractional-order domain for different cases. Neuron synchronization plays an important role in the process of information exchange among coupled neurons. The general formula for the synchronization of different Izhikevich neurons is proposed. Also, the synchronization of two and three neurons are studied at different fractional orders. Furthermore, the fractional-order regular spiking neuron of Izhikevich model is implemented on Xilinx (XC5VLX30T) Virtex 5 FPGA kit using only combinational logic. FPGAs are known for their reconfigurability and parallelism which makes them suitable for large-scale neural network simulations.

Original language	British English
Pages (from-to)	56-69
Number of pages	14
Journal	Microelectronics Journal
Volume	89
DOIs	https://doi.org/10.1016/j.mejo.2019.05.003
State	Published - Jul 2019

Keywords

FPGA
Fractional order
Izhikevich model
Neuron synchronization
Non-standard finite difference

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10.1016/j.mejo.2019.05.003

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title = "Synchronization and FPGA realization of fractional-order Izhikevich neuron model",

abstract = "This paper generalizes the Izhikevich neuron model in the fractional-order domain for better modeling of neuron dynamics. Accurate and computationally efficient numerical techniques such as non-standard finite difference (NSFD) scheme is used to solve the neuron system in the fractional-order domain for different cases. Neuron synchronization plays an important role in the process of information exchange among coupled neurons. The general formula for the synchronization of different Izhikevich neurons is proposed. Also, the synchronization of two and three neurons are studied at different fractional orders. Furthermore, the fractional-order regular spiking neuron of Izhikevich model is implemented on Xilinx (XC5VLX30T) Virtex 5 FPGA kit using only combinational logic. FPGAs are known for their reconfigurability and parallelism which makes them suitable for large-scale neural network simulations.",

keywords = "FPGA, Fractional order, Izhikevich model, Neuron synchronization, Non-standard finite difference",

author = "Tolba, {Mohammed F.} and Elsafty, {Abdulaziz H.} and Mina Armanyos and Said, {Lobna A.} and Madian, {Ahmed H.} and Radwan, {Ahmed G.}",

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doi = "10.1016/j.mejo.2019.05.003",

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AU - Tolba, Mohammed F.

AU - Elsafty, Abdulaziz H.

AU - Armanyos, Mina

AU - Said, Lobna A.

AU - Madian, Ahmed H.

AU - Radwan, Ahmed G.

PY - 2019/7

Y1 - 2019/7

N2 - This paper generalizes the Izhikevich neuron model in the fractional-order domain for better modeling of neuron dynamics. Accurate and computationally efficient numerical techniques such as non-standard finite difference (NSFD) scheme is used to solve the neuron system in the fractional-order domain for different cases. Neuron synchronization plays an important role in the process of information exchange among coupled neurons. The general formula for the synchronization of different Izhikevich neurons is proposed. Also, the synchronization of two and three neurons are studied at different fractional orders. Furthermore, the fractional-order regular spiking neuron of Izhikevich model is implemented on Xilinx (XC5VLX30T) Virtex 5 FPGA kit using only combinational logic. FPGAs are known for their reconfigurability and parallelism which makes them suitable for large-scale neural network simulations.

AB - This paper generalizes the Izhikevich neuron model in the fractional-order domain for better modeling of neuron dynamics. Accurate and computationally efficient numerical techniques such as non-standard finite difference (NSFD) scheme is used to solve the neuron system in the fractional-order domain for different cases. Neuron synchronization plays an important role in the process of information exchange among coupled neurons. The general formula for the synchronization of different Izhikevich neurons is proposed. Also, the synchronization of two and three neurons are studied at different fractional orders. Furthermore, the fractional-order regular spiking neuron of Izhikevich model is implemented on Xilinx (XC5VLX30T) Virtex 5 FPGA kit using only combinational logic. FPGAs are known for their reconfigurability and parallelism which makes them suitable for large-scale neural network simulations.

KW - FPGA

KW - Fractional order

KW - Izhikevich model

KW - Neuron synchronization

KW - Non-standard finite difference

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VL - 89

SP - 56

EP - 69

JO - Microelectronics Journal

JF - Microelectronics Journal

ER -

Synchronization and FPGA realization of fractional-order Izhikevich neuron model

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Keywords

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