Reservoir computing(RC) is a method of neural networks. The parameters to be optimized are between 0 an 1. Since the probability of the quantum states is always between 0 and 1. Therefore, the quantum computing is very suitable to optimize the reservoir computing.
Description
In reservoir computing, there are three matrices between input and output data, Win, W and Wout. The values of the elements of Win, W are chosen randomly. Wout is obtained by the matrix inversion. The aim of this Qiskit project is to use the quantum states to optimize the parameters in Win, W and Wout. The detail can be checked in the following slide.
Abstract
Reservoir computing(RC) is a method of neural networks. The parameters to be optimized are between 0 an 1. Since the probability of the quantum states is always between 0 and 1. Therefore, the quantum computing is very suitable to optimize the reservoir computing.
Description
In reservoir computing, there are three matrices between input and output data, Win, W and Wout. The values of the elements of Win, W are chosen randomly. Wout is obtained by the matrix inversion. The aim of this Qiskit project is to use the quantum states to optimize the parameters in Win, W and Wout. The detail can be checked in the following slide.
Members
@Chii-Chang Chenemail:trich@dop.ncu.edu.twDeliverable
The aim of this pitch in the camp is to build up the algorithm of the reservoir computing using quantum computing for the programming in qiskit.
GitHub repo