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Complex and Quaternion Dense Neural Networks Layers for solving the 4-Bit parity check problem

This repository contains code which evaluates the abilities of Real, Complex, and quaternion based Dense Layers to solve the 4-bit parity check problem. It demonstrates the effectiveness of using other algebras to reduce the size of Neural Networks for a given task.

Requirements

Install requirements for experiments with pip:

pip install numpy Theano keras tensorflow

Depending on your Python installation you might want to use anaconda or other tools.

Experiments

  1. Run models:
python xor.py

Parameters can be modified directly in xor.py, such as:

  • Number of epochs
  • Batch Size
  • Optimizer

Original Paper

This work is based on the original paper of Tohru Nitta: "A Solution to the 4-bit Parity Problem with a Single Quaternary Neuron"

About

A comparison of Real, Complex, and Quaternions valued neurons to solve the 4 Bits parity check.

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  • Python 100.0%