Limits...
A novel memristive multilayer feedforward small-world neural network with its applications in PID control.

Dong Z, Duan S, Hu X, Wang L, Li H - ScientificWorldJournal (2014)

Bottom Line: More specially, a mathematical closed-form charge-governed memristor model is presented with derivation procedures and the corresponding Simulink model is presented, which is an essential block for realizing the memristive synapse and the activation function in electronic neurons.Furthermore, we investigate a more intelligent memristive PID controller by incorporating the proposed MFSNN into intelligent PID control based on the advantages of the memristive MFSNN on computation speed and accuracy.Finally, numerical simulations have demonstrated the effectiveness of the proposed scheme.

View Article: PubMed Central - PubMed

Affiliation: School of Electronics and Information Engineering, Southwest University, Chongqing 400715, China.

ABSTRACT
In this paper, we present an implementation scheme of memristor-based multilayer feedforward small-world neural network (MFSNN) inspirited by the lack of the hardware realization of the MFSNN on account of the need of a large number of electronic neurons and synapses. More specially, a mathematical closed-form charge-governed memristor model is presented with derivation procedures and the corresponding Simulink model is presented, which is an essential block for realizing the memristive synapse and the activation function in electronic neurons. Furthermore, we investigate a more intelligent memristive PID controller by incorporating the proposed MFSNN into intelligent PID control based on the advantages of the memristive MFSNN on computation speed and accuracy. Finally, numerical simulations have demonstrated the effectiveness of the proposed scheme.

Show MeSH
The simplified memristor model. (a) The simplified Simulink model of the memristor. (b) The package of the memristor.
© Copyright Policy - open-access
Related In: Results  -  Collection


getmorefigures.php?uid=PMC4150482&req=5

fig8: The simplified memristor model. (a) The simplified Simulink model of the memristor. (b) The package of the memristor.

Mentions: Based on the constitutive relationship of the memristor, a lot of nonlinear curves can be simulated and substituted [5, 6, 11, 12]. Based on the Simulink model of the nonlinear memristor described in Section 2, we get its simplified Simulink model accordingly as shown in Figure 8(a). Furthermore, we design a package of the memristive device (in Figure 8(b)) which can be considered as a system with single-input and double-output. In this system, the input variable is the current I, and the output variable is the memristance M(t) and charge q(t), respectively.


A novel memristive multilayer feedforward small-world neural network with its applications in PID control.

Dong Z, Duan S, Hu X, Wang L, Li H - ScientificWorldJournal (2014)

The simplified memristor model. (a) The simplified Simulink model of the memristor. (b) The package of the memristor.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4150482&req=5

fig8: The simplified memristor model. (a) The simplified Simulink model of the memristor. (b) The package of the memristor.
Mentions: Based on the constitutive relationship of the memristor, a lot of nonlinear curves can be simulated and substituted [5, 6, 11, 12]. Based on the Simulink model of the nonlinear memristor described in Section 2, we get its simplified Simulink model accordingly as shown in Figure 8(a). Furthermore, we design a package of the memristive device (in Figure 8(b)) which can be considered as a system with single-input and double-output. In this system, the input variable is the current I, and the output variable is the memristance M(t) and charge q(t), respectively.

Bottom Line: More specially, a mathematical closed-form charge-governed memristor model is presented with derivation procedures and the corresponding Simulink model is presented, which is an essential block for realizing the memristive synapse and the activation function in electronic neurons.Furthermore, we investigate a more intelligent memristive PID controller by incorporating the proposed MFSNN into intelligent PID control based on the advantages of the memristive MFSNN on computation speed and accuracy.Finally, numerical simulations have demonstrated the effectiveness of the proposed scheme.

View Article: PubMed Central - PubMed

Affiliation: School of Electronics and Information Engineering, Southwest University, Chongqing 400715, China.

ABSTRACT
In this paper, we present an implementation scheme of memristor-based multilayer feedforward small-world neural network (MFSNN) inspirited by the lack of the hardware realization of the MFSNN on account of the need of a large number of electronic neurons and synapses. More specially, a mathematical closed-form charge-governed memristor model is presented with derivation procedures and the corresponding Simulink model is presented, which is an essential block for realizing the memristive synapse and the activation function in electronic neurons. Furthermore, we investigate a more intelligent memristive PID controller by incorporating the proposed MFSNN into intelligent PID control based on the advantages of the memristive MFSNN on computation speed and accuracy. Finally, numerical simulations have demonstrated the effectiveness of the proposed scheme.

Show MeSH