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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
Constructive procedure of the small-world neural network.
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Related In: Results  -  Collection


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alg1: Constructive procedure of the small-world neural network.

Mentions: Generally, small-world phenomenon indicates that a network has highly concentrated local connections and also includes a few random long connections. In real world, a large number of networks have the small-world effect, such as disease transmission network, social network, and the food chain network [22]. As is known to all, in the classical multilayer feedforward neural network, such as BP network, the ith neuron in the lth layer vil only connects its neighboring neuron sets Vl−1 and Vl+1. In addition, all connections are feedforward and no connections exist between neurons within the same layer. This kind of network can be considered as a regular network. Based on [27] and the construction process of WS small world model, we introduce Algorithm 1 which is used to construct multilayer feedforward neural network model according to the rewiring probability. The specific construction process is given as follows.


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)

Constructive procedure of the small-world neural network.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

alg1: Constructive procedure of the small-world neural network.
Mentions: Generally, small-world phenomenon indicates that a network has highly concentrated local connections and also includes a few random long connections. In real world, a large number of networks have the small-world effect, such as disease transmission network, social network, and the food chain network [22]. As is known to all, in the classical multilayer feedforward neural network, such as BP network, the ith neuron in the lth layer vil only connects its neighboring neuron sets Vl−1 and Vl+1. In addition, all connections are feedforward and no connections exist between neurons within the same layer. This kind of network can be considered as a regular network. Based on [27] and the construction process of WS small world model, we introduce Algorithm 1 which is used to construct multilayer feedforward neural network model according to the rewiring probability. The specific construction process is given as follows.

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