In this work the Generalized Hopfield Neural Network has been adopted to solve the set of SHE equations.
The Hopfield Neural Network is a single layer recurrent neural network that has a feedback arrangement.
Hopfield Neural Network is also known as a gradient type network wherein once the neurons are loaded with initial external inputs the outputs of each neuron undergoes a change these changes are fed back to the neurons and as result a convergent transient happens and the outputs change continuously until the outputs of all the neurons finally attain their respective steady state values.
Bones detection from chicken breast meat using a Competitive Hopfield Neural Network and fuzzy filtering, in Proc.
Segmentation of dual-band images of x-ray chicken breast using a Competitive Hopfield Neural Network, in Proc.
Key words: image processing, X-ray imaging, Hopfield neural networks, fuzzy logic
Sun, "Mean square exponential stability of stochastic delayed Hopfield neural networks
," Physics Letters, Section A: General, Atomic and Solid State Physics, vol.
Large-scale economic dispatch using an improved hopfield neural network.
New approach for solving optimization problems in economic load dispatch using hopfield neural networks // 2000 Canadian Conference on Electrical and Computer Engineering.
Delay-dependent global stability results for delayed Hopfield neural networks.
Global exponential stability of Hopfield neural networks with distributed delays.
New LMI conditions for delay-dependent asymptotic stability of delayed Hopfield neural networks
, Neurocomputing, vol.