5.1Hopfieldneuralnetwork In1982,HopfieldJJbroughtforwardasinglelayerfeedbacknetworkcomposedofnonlinearcomponent.Feedbacknetworkisanonlineardynamicsystem.•NonlineardifferenceequationDiscreteHNN(DHNN)•differentialequationContinuousHNN(CHNN)Applications:associativememoryorclassificationcomputingforoptimization 5.1.1Discrete...
Method for feedback linearization of neural networks and neural network incorporating same A method for linearization of feedback in neural networks, and a neural network incorporating the feedback linearization method are presented. Control action is used to achieve tracking performance for a state-fee...
This problem is addressed by training an artificial neural network to represent the simulation output. This approach is demonstrated on the simulated extrusion of a plain carbon steel rod 展开 关键词: extrusion materials processing metal forming output feedback process control ...
1.14.2Feedback neural network Feedback neural network allows the information to move in both directions as close loop network architecture as shown inFig. 15. The output of network influenced the input to achieve the objective function of network by back propagating the error information. However ...
Two devices (802, 804) in wireless communication implement a soft transmission feedback scheme. A data-sending device (802) wirelessly communicates a first transmission (822) representing a data block (818) and generated using one or more neural networks (808) to a data-receiving device (804)...
In this blog post we explore the differences between deed-forward and feedback neural networks, look at CNNs and RNNs, examine popular examples of Neural Net…
First results from off-line tests suggest the potential of implementing new operational autoscaling software in the worldwide Digisonde network. 展开 关键词: Artificial neural networks Rotors Atmospheric modeling Robustness Earth Atmospheric waves Meteorology ...
This method may, thus, supplement standard techniques (e.g. error backprop) adding a new quality to network learning. 展开 关键词: Deep learning Feedback Transfer entropy Convolutional neural network DOI: 10.1016/j.neunet.2019.12.004 被引量: 2 年份: 2020 ...
neural network as part of the standard NARX architecture, as shown in the left figure below. Because the true output is available during the training of the network, you could create a series-parallel architecture (see [NaPa91]), in which the true output is used instead of feeding back ...
In particular, the autapse connects the soma to a self-feedback loop that transmits information to itself. As shown in Fig. 1, the autapses in the brain act on the membrane potential to help regulate spike precision and network activity in a time-delayed self-feedback. Inspired by the ...