Understanding Compressive Sensing

Speaker:  Andriyan Bayu Suksmono – Bandung, Indonesia
Topic(s):  Computational Theory, Algorithms and Mathematics , Applied Computing

Abstract

Compressed Sensing or Compressive Sampling (CS) is a new paradigm in modern signal processing and sensing. Rooted in the uncertainty principle—CS provides a powerful framework for reconstructing signals from highly incomplete measurements. This presentation introduces the core concepts of CS and its theoretical foundations, supported by intuitive illustrations that facilitate understanding of the concept. Several examples will be presented to highlight the broad spectrum of applications and the transformative potential of CS across scientific and engineering domains.

About this Lecture

Number of Slides:  50
Duration:  45 minutes
Languages Available:  English
Last Updated:  03/12/2025

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