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Sparse Representations in Signal and Image Processing - Fundamentals, Certificate

Sparse Representations in Signal and Image Processing - Fundamentals, Certificate

  • Anytime
    Application Deadline
  • 35 days
    Duration
Online
EdX is an online learning platform trusted by over 12 million users offering the Sparse Representations in Signal and Image Processing - Fundamentals Certificate in collaboration with IsraelX.  Learn about the field of sparse representations by understanding its fundamental theoretical and algorithmic foundations.

About

The Sparse Representations in Signal and Image Processing - Fundamentals Certificate is part of the Sparse Representations in Signal and Image Processing Certificate from EdX in partnership with IsraelX.

This course introduces the fundamentals of the field of sparse representations, starting with its theoretical concepts, and systematically presenting its key achievements. We will touch on theory and numerical algorithms.

Modeling data is the way we – scientists – believe that information should be explained and handled. Indeed, models play a central role in practically every task in signal and image processing. Sparse representation theory puts forward an emerging, highly effective, and universal such model. Its core idea is the description of the data as a linear combination of few building blocks – atoms – taken from a pre-defined dictionary of such fundamental elements.

A series of theoretical problems arise in deploying this seemingly simple model to data sources, leading to fascinating new results in linear algebra, approximation theory, optimization, and machine learning. In this course you will learn of these achievements, which serve as the foundations for a revolution that took place in signal and image processing in recent years.

What you'll learn

  • About the fundamental ideas of sparse representation theory – exploring properties such as uniqueness, equivalence, and stability.
  • About sparse coding algorithms and their proven ability to perform well.

Detailed Programme Facts

  • Programme intensity Part-time
    • Average part-time duration 35 days
    • Intensity 5 hrs/week
    • Part-time variant
      Flexible
    • Duration description

      Length: 5 weeks Effort: 5 to 6 hours per week

  • Languages
    • English
  • Delivery mode
    Online

Programme Structure

This program is composed from two separate parts:

  • Part 1: Sparse Representations in Signal and Image Processing: Fundamentals.
  • Part 2: Sparse Representations in Image Processing: From Theory to Practice.
  • While we recommend taking both courses, each of them can be taken independently of the other. The duration of each course is five weeks, and each part includes: (i) knowledge-check questions and discussions, (ii) series of quizzes, and (iii) Matlab programming projects. Each course will be graded separately, using the average grades of the questions/discussions [K] quizzes [Q], and projects [P], by Final-Grade = 0.1K + 0.5Q + 0.4P.

    Lecturers

    • Michael Elad - Professor of Computer Science, Technion, Israel Institute of Technology

    English Language Requirements

    This programme requires students to demonstrate proficiency in English.

    Academic Requirements

    Prerequisites

    Advanced knowledge on linear algebra and optimization; basic familiarity with signal and image processing.

    Tuition Fee

    • International Applies to you

      99 USD/full
      Tuition Fee
      Based on the original amount of 99 USD for the full programme and a duration of 35 days.
    • National Applies to you

      99 USD/full
      Tuition Fee
      Based on the original amount of 99 USD for the full programme and a duration of 35 days.
    We've labeled the tuition fee that applies to you because we think you are from and prefer over other currencies.
    5% discount coupon: Z7LZNQ4TN3B2JTWU valid for any free course + certificate upgrade

    Funding

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