Advanced · Neural Networks
Reservoir computing
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. A computing framework using fixed, complex dynamical systems to process input signals.
Technical Definition
A computing framework using fixed, complex dynamical systems to process input signals.
How it works
Reservoir computing is a computational paradigm that uses a fixed, intricate dynamical system, called a 'reservoir,' to map input signals into a higher-dimensional space. A simple 'readout' mechanism is then trained to interpret the reservoir's state and produce the desired output. This approach significantly reduces training complexity, as only the readout is trained.
Related Concepts
- Recurrent Neural Network (RNN) — A neural network with loops that maintain hidden state, designed to process sequential data like text and time series.
- Echo state network (ESN) — A type of recurrent neural network with a fixed, randomly connected hidden layer, where only output weights are learned to reproduce temporal patterns.