Hopfield network - significado y definición. Qué es Hopfield network
Diclib.com
Diccionario ChatGPT
Ingrese una palabra o frase en cualquier idioma 👆
Idioma:

Traducción y análisis de palabras por inteligencia artificial ChatGPT

En esta página puede obtener un análisis detallado de una palabra o frase, producido utilizando la mejor tecnología de inteligencia artificial hasta la fecha:

  • cómo se usa la palabra
  • frecuencia de uso
  • se utiliza con más frecuencia en el habla oral o escrita
  • opciones de traducción
  • ejemplos de uso (varias frases con traducción)
  • etimología

Qué (quién) es Hopfield network - definición

RECURRENT NEURAL NETWORK
Hopfield nets; Hopfield model; Hopfield neural network; Hopfield networks; Hopfield net; Hopfield Network; Training Hopfield networks
  • smooth]] enough" function.<ref name=":1" />
  • Energy Landscape of a Hopfield Network, highlighting the current state of the network (up the hill), an attractor state to which it will eventually converge, a minimum energy level and a basin of attraction shaded in green. Note how the update of the Hopfield Network is always going down in Energy.
  • Fig. 3: The connectivity diagram of the fully-connected modern Hopfield network consisting of five neurons. The synaptic weights are described by a symmetric matrix <math>W_{IJ}</math>.
  • Fig. 4: The connectivity diagram of the layered Hierarchical Associative Memory network.<ref name=":5" /> Each layer can have different number of neurons, different activation function, and different time scales. The feedforward weights and feedback weights are equal.
  • Fig. 1: An example of a continuous modern Hopfield network with <math display="inline">N_f=5</math>  feature neurons and <math>N_\text{mem}=11</math> memory (hidden) neurons with symmetric synaptic connections between them.

Hopfield network         
<artificial intelligence> (Or "Hopfield model") A kind of neural network investigated by John Hopfield in the early 1980s. The Hopfield network has no special input or output neurons (see McCulloch-Pitts), but all are both input and output, and all are connected to all others in both directions (with equal weights in the two directions). Input is applied simultaneously to all neurons which then output to each other and the process continues until a stable state is reached, which represents the network output. (1997-10-11)
Hopfield network         
A Hopfield network (or Ising model of a neural network or Ising–Lenz–Little model) is a form of recurrent artificial neural network and a type of spin glass system popularised by John Hopfield in 1982 as described earlier by Little in 1974 based on Ernst Ising's work with Wilhelm Lenz on the Ising model. Hopfield networks serve as content-addressable ("associative") memory systems with binary threshold nodes, or with continuous variables.
Hopfield model         

Wikipedia

Hopfield network

A Hopfield network (or Ising model of a neural network or Ising–Lenz–Little model) is a form of recurrent artificial neural network and a type of spin glass system popularised by John Hopfield in 1982 as described by Shun'ichi Amari in 1972 and by Little in 1974 based on Ernst Ising's work with Wilhelm Lenz on the Ising model. Hopfield networks serve as content-addressable ("associative") memory systems with binary threshold nodes, or with continuous variables. Hopfield networks also provide a model for understanding human memory.