Welcome to Lecture 20 of the course "Digital Signal Processing" by Prof.David Koilpllai
Full Course: https://study.iitm.ac.in/es/course_pages/EE3101.html

Video Overview
In this lecture you will learn about the concept of causality in discrete time systems and why it is important for analyzing and designing filters in signal processing. We will define what a causal system is and use examples like the averaging filter to illustrate this concept clearly. The lecture also reviews linearity and time invariance to strengthen your understanding of LTI systems. You will learn how to derive the impulse response of an averaging filter and extend this to understand moving average MA filters. We will also discuss the condition that an LTI system must satisfy to be causal based on its impulse response and explore methods to convert non causal filters into causal filters for practical implementation. Reviewing the properties of LTI systems and their characterization using impulse response is recommended for your next learning session.

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