Neurons: The Hopfield network has a finite set of neurons x(i),1≤i≤N, which serve as processing units. Each neuron has a value (or state) at time t described by xt(i). A neuron in the Hopfield net has one of the two states, either -1 or +1; that is, xt(i)∈{-1,+1}...
Hopfield neural network HOPG HOPI HOPIF HOPIN HOPING HOPL HOPLT HOPM HOPN HOPOS HOPP HOPPS HOPR HOPS HOPSEC HOPT HOPTE HopTel HOPTF HOPTR HOPU HOPWA HOPWF HOQ HOR ▼ Complete English Grammar Rules is now available in paperback and eBook formats. ...
In our previous work, the eliminating-highest-error (EHE) criterion was proposed for the modified Hopfield neural network (MHNN) for image restoration and reconstruction. The performance of the MHNN is considerably improved by the EHE criterion as shown in many simulations. In inspiration of revea...
ZJ Lee,CY Lee,SF Su - 《Applied Soft Computing》 被引量: 410发表: 2003年 Learning viewpoint-invariant face representations from visual experience in an attractor network In natural visual experience, different views of an object or face tend to appear in close temporal proximity as an animal ...
We present an improved method based on the Hopfield neural network for RNA secondary structure prediction in this study. The proposed method adjusts two pa... YQ Che,Q Cao,Z Tang - 《International Journal of Soft Computing》 被引量: 0发表: 2006年 An Efficient Algorithm Based on Hopfield Ne...
Hopfield neural networkArtificial neuronSpin-glassMolecular magnetSummary: Paper considers three Hopfield based architectures in the stereo matching problem solving. Together with classical analogue Hopfield structure two novel architectures are examined: Hybrid-Maximum Neural Network and Self Correcting Neural ...
Short term load forecasting models in Czech Republic using soft computing techniques This paper presents a comparative study of six soft computing models namely multilayer perceptron networks, Elman recurrent neural network, radial basis function network, Hopfield model, fuzzy inference system and hybrid ...
The following sections are included:IntroductionNeural Network PrinciplesHistory of Neural NetworksProperties of Neural NetworksApplications of Neural Netw... MT Hagan,HB Demuth - Soft Computing In Systems And Control Technology 被引量: 136发表: 1999年 Global robust asymptotic stability analysis of uncert...
An important difference between brains and deep neural networks is the way they learn. Nervous systems learn online where a stream of noisy data points are presented in a non-independent, identically distributed way. Further, synaptic plasticity in the b
Vo Ngoc Dieu,Peter Schegner. Applied Soft Computing . 2013Dieu V.N. and Schegner P., (2013), Augmented Lagrange Hopfield network initialized by quadratic programming for economic dispatch with piecewise quadratic cost functions and prohibited zones, Applied Soft Computing, 13(1), 292-301....