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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 Simulink model of the nonlinear memristor.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig4: The Simulink model of the nonlinear memristor.

Mentions: For the sake of analyzing the characteristics of the memristor model comprehensively, a Simulink model is built upon (2)–(12) and illustrated in Figure 4. The model mainly consists of input and output modules, internal operation modules (multipliers, adders, and modules), and parameter control modules. The model parameters are the same as those in Figure 3. The signal stimulus applied into the memristor is a sinusoidal current source with amplitude of 0.5 mA and frequency of 1 Hz.


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 Simulink model of the nonlinear memristor.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig4: The Simulink model of the nonlinear memristor.
Mentions: For the sake of analyzing the characteristics of the memristor model comprehensively, a Simulink model is built upon (2)–(12) and illustrated in Figure 4. The model mainly consists of input and output modules, internal operation modules (multipliers, adders, and modules), and parameter control modules. The model parameters are the same as those in Figure 3. The signal stimulus applied into the memristor is a sinusoidal current source with amplitude of 0.5 mA and frequency of 1 Hz.

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