Digital Filters - FIR & IIR - Edu Lowcostlivin

Course Feature

Cost

Paid
Provider

Udemy
Certificate

Paid Certification
Language

English
Start Date

2023-06-23
Learners

No Information
Duration

No Information
Instructor

Sarita Bopalkar

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4.4

415 Ratings

This course is perfect for students, engineers, and academicians who want to learn the basics of Digital Filters and how to design them in Python. It covers Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters, with theory and practical implementation. With step-by-step instructions and plenty of examples, this course will give you the confidence to design filters for different DSP applications. It also covers the characteristics of DT-LTI systems and various FIR and IIR filter design techniques. Don't miss out on this opportunity to learn the fundamentals of Digital Filters and gain the skills to apply them in real-world scenarios.

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Course Overview

❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [July 24th, 2023]

Learners of this course will gain a comprehensive understanding of digital filters, including Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters. They will gain experience in designing filters using various methods, such as windowing and frequency sampling, and will be able to apply these filters to a variety of DSP applications. Furthermore, they will gain practical experience in implementing these filters in Python. With this knowledge and experience, learners will be able to confidently design and implement digital filters in their own projects.

Course Syllabus

Course Overview

Introduction to DT-LTI system

FIR Filter

FIR Filter Desiging by Windowing Method

Design FIR filter by Frequency Sampling Method

Study and compare window function using Python

Design FIR Filter using Python

IIR Filter

Butterworth Filter

Design Butterworth filter using Python

Chebyshev Filter

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