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Digital Filter Web-Based Project is a web application that allows users to create and apply custom digital filters to signals stored in CSV format. The application is built using HTML, CSS, JavaScript, and D3.js, a JavaScript library for data visualization.

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Digital Filter Web Based Project

Introduction

Digital Filter Web-Based Project is a web application that allows users to create and apply custom digital filters to signals stored in CSV format. The application is built using HTML, CSS, JavaScript, and D3.js, a JavaScript library for data visualization.

Features

  1. Signal Upload: Users can upload signal data stored in CSV format.
  2. Filter Creation: Users can create custom digital filters by selecting filter type, cutoff frequency, and other filter parameters.
  3. Filter Application: Users can apply the custom digital filter to the uploaded signal data.
  4. Signal Visualization: The application provides users with visual representations of the signal data and the filtered signal data.
  5. Exporting: Users can export the filtered signal data in CSV format.

Tech Stack

  1. HTML: The application uses HTML to create the structure and content of the web pages.
  2. CSS: The application uses CSS to style the web pages.
  3. JavaScript: The application uses JavaScript to implement the filter creation and application functionality.
  4. D3.js: The application uses D3.js to create visualizations of the signal data.

Usage

  • Launch the application in your web browser.
  • Upload a signal file in CSV format by clicking the "Upload Signal" button.
  • Create a custom digital filter by selecting filter type, cutoff frequency, and other filter parameters.
  • Apply the custom digital filter to the uploaded signal data by clicking the "Apply Filter" button.
  • View the visual representations of the signal data and the filtered signal data.
  • Export the filtered signal data in CSV format by clicking the "Export" button.

About

Digital Filter Web-Based Project is a web application that allows users to create and apply custom digital filters to signals stored in CSV format. The application is built using HTML, CSS, JavaScript, and D3.js, a JavaScript library for data visualization.

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