A Low Dimensional Description of Globally Coupled Heterogeneous Neural Networks of Excitatory and Inhibitory Neurons.
Roxana A. StefanescuViktor K. JirsaPublished in: PLoS Comput. Biol. (2008)
Keyphrases
- neural network
- low dimensional
- high dimensional
- activation function
- hidden layer
- manifold learning
- high dimensional data
- input space
- back propagation
- dimensionality reduction
- principal component analysis
- artificial neural networks
- pattern recognition
- fuzzy logic
- multilayer perceptron
- data points
- learning rules
- high level
- euclidean space
- neural network structure
- neural models
- training algorithm
- associative memory
- feed forward
- data sets
- recurrent neural networks
- linear subspace
- genetic algorithm
- feed forward neural networks
- connection weights
- receptive fields
- recognizing facial expressions
- hodgkin huxley
- spiking neurons
- nonlinear dimensionality reduction
- multidimensional scaling
- spiking neural networks
- feedforward neural networks
- visual cortex
- multi layer perceptron
- network architecture