Hopfield model

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Hopfield network

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As for troposphere, we use Hopfield model to get the tropospheric refractive index.

In this paper, we use the Hopfield model [12], which includes mainly two parts.

Multiband microwave imaging analysis of ionosphere and troposphere refraction for spaceborne SAR

They cover the Hopfield model, a network counting chimes, associative memory networks at low rates, towards networks of spiking neurons, the Miyashita correlations, learning in networks with discrete synapses, the Behavioral and Brain Science review, dynamics of networks of spiking neurons, electronic implementations, prospective activity, multi-item working memory, learning with spike-driven plastic synapses, and familiarity recognition.

Selected papers of Daniel Amit (1938-2007)

Hopfield model has been used for the estimation of tropospheric delay [4].

Determination of GPS receiver position using Multivariate Newton-Raphson Technique for over specified cases

The computation of the ZHD may be done with the aid of the models developed so far; we mention here the Hopfield model, the Saastamoinen model, etc.

Estimating the precipitable water vapour using Romania's permanent GPS network

An FCM Works as a mono layer neural network similar to the Hopfield model, but with auto concurrent connections and step, sigmoid and linear activation functions.

Realistic ecosystem modelling with fuzzy cognitive maps

The hydrostatic component of the troposphere can be mitigated by a number of models like the Saastamoinen or Hopfield model. One can use these models utilizing standard atmosphere parameters or by entering into model surface meteorological data from global or regional numerical meteorological models such as European Centre for Medium-Range Weather Forecast (ECMWF), the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) or Global Pressure and Temperature (GPT) (Boehm et al., 2007; Kalita et al., 2014).

GPS/GLONASS precise point positioning with IGS real-time service products

The Hopfield model is used to take into account the influence of the troposphere.

LOCAL GEODYNAMICS OF THE TERRITORY OF DNIESTER PUMPED STORAGE POWER PLANT

This motivates our development of a computational framework, using the Hopfield model for associative memory, which can provide a platform to study the conditions in which an auxiliary external network may prevent and/or reverse TBI and neurodegenerative impairments.

Hopfield Model. In our autoassociative memory network, coupled artificial neurons respond to meaningful external queues with stable, collective activity patterns (where 1 [less than or equal to] [mu] [less than or equal to] 20).

Preventing Neurodegenerative Memory Loss in Hopfield Neuronal Networks Using Cerebral Organoids or External Microelectronics

Perceptron is aimed at physical systems and does not consider abstract population characteristics where the Hopfield model does.

Neuronal ensemble decoding using a dynamical maximum entropy model

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