Neural-Network-Logic-Gates

CONTENTS OF THIS FILE

• Introduction
• Requirements
• Installation
• Directory Structure
• Usage
• Credits

Introduction

Neural networks are series of algorithms that are designed to mimic the way the human brain operates. Neural networks refer to systems of neurons, either organic or artificial in nature. Just like a human brain, neural network adapts itselt according to the given input and the desired output.

This assignment focuses on implementation of logic gates using neural networks. The experiments were conducted for 500 epochs for each gate and their respective error vs. epoch curve has been plotted.

Requirements

1. Python 3
2. Numpy
3. Matplotlib
4. Pandas
5. Jupyter Notebook

Installation

1. Python

Step 1: Visit and download Python from https://www.python.org/downloads/ Step 2: Install and add Python to path

2. Numpy

In command prompt

pip install numpy

3. Matplotlib

In command prompt

pip install matplotlib

4. Pandas

In command prompt

pip install pandas

5. Jupyter

In command prompt

pip install jupyterlab

For conda users

conda install -c conda-forge jupyterlab

To start Jupyter type

jupyter notebook

Directory Structure

.
├── output                        # Output files
│   ├── output_1_and_gate.png
│   ├── output_2_or_gate.png
│   ├── output_3_nand_gate.png
│   ├── output_4_nor_gate.png
│   ├── output_5_xor_gate.png
│   ├── output_6_xnor_gate.png 
├── src                           # Source files
│   ├── neural_network_LG.ipynb   # Jupyter Notebook
├── LICENSE
└── README.md

Usage

The project folder contains two folder, src and output. The source code (neural_network_LG.ipynb) is present in the src folder. The screenshots of the curves are present in the output folder with theor respective names. The documentation.pdf file provides the documentation, i.e. the pdf version of the notebook.

Credits

Author: Ajay Biswas

Email: 220cs2184@nitrkl.ac.in

M.Tech. Information Security, NIT Rourkela, India.

2nd Semester