Basing on the multilayer feedback BP neural network model obtained through circuit analogue and energy function , this paper proves the stability ot feedback BP network associative memory process. The proof of associative memory process stability of feedback network is given, as well as relative ...
Beyond feedforward models trained by backpropagation: a practical training tool for a more efficient universal approximator. Cellular simultaneous recurrent neural network (SRN) has been shown to be a function approximator more powerful than the multilayer perceptron (MLP). This ... Roman,Ilin,Ro...
cross_decomposition datasets decomposition ensemble experimental externals feature_extraction feature_selection gaussian_process impute inspection linear_model manifold metrics mixture model_selection neighbors neural_network tests __init__.py _base.py
Neural network-based decision feedback equaliser with lattice structure The effect of whitening the input data in a multilayer perceptron-based decision feedback equaliser (DFE) is evaluated. It is shown from computer simulatio... Shafi,A.,Zerguine,... - 《Electronics Letters》 被引量: 10发表...
cross_decomposition datasets decomposition ensemble experimental externals feature_extraction feature_selection gaussian_process impute inspection linear_model manifold metrics mixture model_selection neighbors neural_network tests __init__.py _base.py
Neural-network control of nonaffine nonlinear system with zero dynamics by state and output feedback This paper focuses on adaptive control of nonaffine nonlinear systems with zero dynamics using multilayer neural networks. Through neural network approxima... SS Ge,Z Jin - 《IEEE Transactions on ...
Twitter Google Share on Facebook multilayer perceptron Acronyms A network composed of more than one layer of neurons, with some or all of the outputs of each layer connected to one or more of the inputs of another layer. The first layer is called the input layer, the last one is the ou...
Whereas the addition of feedback connections to the network did not qualitatively change the behavior, the presence of recurrent connections strongly supported propagation. In the framework of information theory, the channel capacity of a neuron is related to the range of firing that the neuron can...
D. Detection of multistability, bifurcations, and hysteresis in a large class of biological positive-feedback systems. Proc. Natl Acad. Sci. USA 101, 1822–1827 (2004). Article ADS Google Scholar Helbing, D. Globally networked risks and how to respond. Nature 497, 51–59 (2013). Article...
The in situ online training was composed of two stages: feedforward inference and feedback weight update. The multilayer inference was performed layer by layer sequentially. The input voltage vector to the first layer was a feature vector from the dataset, while the input vector for the subsequen...