| Safe Haskell | None |
|---|---|
| Language | Haskell2010 |
RC.NTC
Description
Nonlinear transient computing
This module was developed as a part of author's PhD project: https://www.researchgate.net/project/Theory-and-Modeling-of-Complex-Nonlinear-Delay-Dynamics-Applied-to-Neuromorphic-Computing
- new :: StdGen -> NTCParameters -> (Int, Int, Int) -> NTC
- learn :: NTC -> Int -> Matrix Double -> Matrix Double -> Either String NTC
- predict :: NTC -> Int -> Matrix Double -> Either String (Matrix Double)
- par0 :: NTCParameters
- data NTCParameters = Par {
- _preprocess :: Matrix Double -> Matrix Double
- _inputWeightsRange :: (Double, Double)
- _inputWeightsGenerator :: StdGen -> (Int, Int) -> (Double, Double) -> Matrix Double
- _postprocess :: Matrix Double -> Matrix Double
- _reservoirModel :: Par
- data Par :: *
- data BandpassFiltering :: * = BandpassFiltering {}
Documentation
Arguments
| :: StdGen | |
| -> NTCParameters | |
| -> (Int, Int, Int) | Input dimension, network nodes, and output dimension |
| -> NTC |
Creates an untrained NTC network
Arguments
| :: NTC | |
| -> Int | Discard the first N points |
| -> Matrix Double | Input matrix of features rows and observations columns |
| -> Matrix Double | Desired output matrix of observations columns |
| -> Either String NTC |
NTC training: learn the readout weights offline
Arguments
| :: NTC | Trained network |
| -> Int | Washout (forget) points |
| -> Matrix Double | Input matrix where measurements are columns and features are rows |
| -> Either String (Matrix Double) | Either error string or predicted output |
Run prediction using a "clean" (uninitialized) reservoir and then forget the reservoir's state. This can be used for both forecasting and classification tasks.
par0 :: NTCParameters Source #
Default NTC parameters
data NTCParameters Source #
Customizable NTC parameters
Constructors
| Par | |
Fields
| |
Model parameters
data BandpassFiltering :: * #
Bandpass filter (linear) parameters
Constructors
| BandpassFiltering | |
Instances