Signal processing using digital computers and special purpose digital hardware has taken on major significance in the past decade. The inherent flexibility of digital elements permits the utilization of a variety of sophisticated signal processing techniques which had previously been impractical to implement. Advances in integrated circuit technology have had a major impact on the technical areas to which digital signal processing techniques and hardware are being applied. Applications of these techniques are now prevalent in such diverse areas as biomedical engineering, acoustics, sonar, radar, seismology, speech communication, telephony, nuclear science, image processing and many others. Thus, a thorough understanding of digital signal processing fundamentals and techniques is essential for anyone concerned with signal processing applications.
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Digital Signal Processing
Introduction to Digital Signal Processing
Digital Signal Processing is the branch of engineering that, in the space of just a few decades, has enabled unprecedented levels of interpersonal communication and of on-demand entertainment.
Who is this course for? This course is primarily designed for STEM undergraduates who have already completed classes in calculus and linear algebra. It is also ideal as a Digital Signal Processing primer for students interested in a mathematically solid introduction to the subject.
Know a few basic points on getting started with digital signal processing. Install MATLAB on your System along with the necessary toolboxes and get ready to learn amazing programs brought to you by MATLAB Helper ®
Transform Analysis of Linear Time Invariant System
Find the impulse response of any discrete LTI system when the transfer function of the system is H(z) is given using the Z-transformation Method.
Computation of Linear and Circular Convolution using DFT techniques also we see why the answer differs in both cases and how to make them same.
The Discrete Fourier Transform and Efficient Computation
Computation of Discrete Fourier Transform and Fast Fourier Transformation along with their Inverse Transformations using definition and MATLAB Functions
Design of Digital filters and Implementation
Find out how to design and compute a Butterworth IIR Filter by Bilinear Transformation Method using MATLAB along with a theoretical explanation.
Find out how to design and compute a Chebyshev's IIR Filter by Bilinear Transformation Method using MATLAB along with the theoretical explanation.
Find out how to design and compute a Butterworth IIR Filter by Impulse Invariant Method using MATLAB along with theoretical explanation.
Find out how to design and compute a Chebyshev's IIR Filter by Impulse Invariant Transformation Method using MATLAB along with theoretical explanation.
Finite Impulse Response (FIR) Filters using Rectangular Window Method
Design and Finite Impulse Response (FIR) Filter using Rectangular Windowing Method in MATLAB along with illustrative example and code.
Multi rate Signal Processing
The Fourier transform of the auto-correlation sequence of any random process gives power spectral density or power spectrum of that signal
The process of converting a signal from one sampling rate to another sampling rate is called as sampling rate conversion [Decimation / Interpolation]
To be eligible for Certification for this course, you need to pass this test with a score of 75% or more.
About the teacher
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