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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

The Introduction to Adaptive Signal Processing certification course delves into the vital realm of adaptive filters, pivotal in contemporary signal processing, communication, and control applications. Its versatility in handling unpredictable data conditions makes it indispensable in areas like radar, sonar, wireless communications, and more.

Tailored for students in various disciplines, the Introduction to Adaptive Signal Processing certification by Swayam introduces adaptive filters, closely tied to neural networks and machine learning. The eight-week elective course, backed by industry giants like Qualcomm and DRDO, offers a foundational understanding, preparing participants for advanced studies in this field.

The Highlights

Elective Online Course
8 Weeks Duration
Offered by IIT Kharagpur

Programme Offerings

Certificate of completion
Practical Learning
Hands-on Experience

Courses and Certificate Fees

Fees Informations	Certificate Availability	Certificate Providing Authority
INR 1000	yes	IIT Kharagpur

The Introduction to Adaptive Signal Processing certification fees is free. However, if you want a certificate, you must register and take the proctored exam at designated centers, which is optional and comes with a fee of Rs 1000.

Introduction to Adaptive Signal Processing Certification Fee Structure

Particulars	Total Fees
Introduction to Adaptive Signal Processing (exam)	Rs 1000/-

Eligibility Criteria

Academic Qualifications

The Introduction to Adaptive Signal Processing certification course is intended for students in Electrical Engineering, Electronics, Communication, Instrumentation, IT, Computer Science, Geophysics, and Statistics, requiring a basic grasp of Signals and Systems and/or Digital Signal Processing.

Certification Qualifying Details

To receive the Introduction to Adaptive Signal Processing certification by Swayam, you need a minimum average assignment score of 10/25 and an exam score of 30/75.

What you will learn

After completing the Introduction to Adaptive Signal Processing certification syllabus, you will gain a comprehensive understanding of adaptive filters and their pivotal role in signal processing, communication, and control applications. You will also delve into the mathematical concepts necessary for grasping adaptive filters.

Upon completion of the Introduction to Adaptive Signal Processing training, you will explore a diverse array of applications, including radar, sonar, wireless communications, speech and audio processing, instrumentation, and exploration geophysics.

Who it is for

Electrical EngineerData AnalystData ScientistIT ConsultantMachine Learning EngineerResearch Scientist

The Introduction to Adaptive Signal Processing online course is suitable for students in disciplines such as Electrical Engineering, Electronics and Communication Engineering, Instrumentation Engineering, Information Technology, Computer Science, Geophysics, and Statistics. This course is also beneficial for:

Admission Details

Follow these steps to join the Introduction to Adaptive Signal Processing classes:

Step 1: Browse the URL below:

https://onlinecourses.nptel.ac.in/noc23_ee138/preview

Step 2: Click on the “Sign-in/ Register” button

Step 3: Fill out the necessary details and submit the form

The Syllabus

Basic principle of adaptive filtering and estimation; probability, random variables, conditional and joint probability densities, statistical independence, correlation and covariance.

Complex random variables, random vectors, correlation and covariance matrices, properties of Hermitian matrices (e.g., correlation/covariance matrices), positive definite forms, multivariate Gaussian density

Concepts of random processes, wide sense stationary (WSS) processes and their correlation structures, power spectral density, parametric modeling of WSS processes – AR, MA and ARMA processes.

Optimal FIR filters, real and complex valued optimal filters, method of steepest descent

Least mean square (LMS) algorithm; convergence of LMS algorithm; normalized LMS, affine projection

Examples of adaptive filters: channel equalization, echo cancellation, interference cancellation, line enhancement, beamforming etc.

Limitations of LMS algorithm, formulation of recursive least squares (RLS) based adaptive filters, Moore-Penrose pseudo inverse, matrix inversion lemma

Development of the RLS transversal adaptive filter, properties, variants of the RLS family.

Evaluation process

The Introduction to Adaptive Signal Processing certification offers an optional exam. Your final score is determined by averaging the best 8 out of 12 assignments (25%) and your proctored exam score (75%).

Instructors

IIT Kharagpur Frequently Asked Questions (FAQ's)

1: What are the prerequisites for the Introduction to Adaptive Signal Processing online course?

The prerequisites for this course include a basic understanding of Signals and Systems and/or Digital Signal Processing.

2: Can students from non-engineering backgrounds enroll in the Introduction to Adaptive Signal Processing certification course?

While the course is primarily designed for engineering disciplines, individuals from related fields such as Statistics are also welcome, provided they meet the prerequisite requirements.

3: How long is the duration of the Introduction to Adaptive Signal Processing online course?

The course spans eight weeks, providing a comprehensive yet concise exploration of adaptive filters and related concepts.

4: What career paths can I pursue after completing the Introduction to Adaptive Signal Processing training?

Graduates of this course can pursue careers in Signal Processing, Communication Systems, Control Systems, Machine Learning, Geophysics, Research, and various other related fields.

5: Are there any industry connections or support for this course?

Yes, the course has industry support from organizations such as Qualcomm, Signion, LRDE (DRDO), BEL, and DLRL (DRDO), ensuring its relevance to real-world applications and potential networking opportunities.