Echo state network
Encyclopedia
The echo state network is a recurrent neural network
with a sparsely connected hidden layer (with typically 1% connectivity). The connectivity and weights of hidden neurons are randomly assigned and are fixed. The weights of output neurons can be learned so that the network can (re)produce specific temporal patterns.
The main interest of this network is that although its behaviour is non-linear, the only parameters are the weights of the output layer. The error function is thus quadratic with respect to the parameter vector and can be differentiated easily to a linear system.
Recurrent neural network
A recurrent neural network is a class of neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process...
with a sparsely connected hidden layer (with typically 1% connectivity). The connectivity and weights of hidden neurons are randomly assigned and are fixed. The weights of output neurons can be learned so that the network can (re)produce specific temporal patterns.
The main interest of this network is that although its behaviour is non-linear, the only parameters are the weights of the output layer. The error function is thus quadratic with respect to the parameter vector and can be differentiated easily to a linear system.
See also
- Liquid-state machine: a similar concept with generalized signal and network.
- Reservoir computingReservoir computingReservoir computing is a framework for computation like a neural network.Typically an input signal is fed into a fixed dynamical system called reservoir and the dynamics of the reservoir map the input to a higher dimension....
- aureservoir: an efficient C++ library for various kinds of echo state networks with python/numpy bindings.