Basic Elements of a DSP system, Typical DSP applications, Finite-length discrete transforms, Orthogonal transforms – The Discrete Fourier Transform: DFT as a linear transformation (Matrix relations), Relationship of the DFT to other transforms, IDFT, Properties of DFT and examples. Circular convolution, Linear Filtering methods based on the DFT, linear convolution using circular convolution, Filtering of long data sequences, overlap save and overlap add methods, Frequency Analysis of Signals using the DFT (concept only required)
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Introduction to Digital signal processing
Basic blocks of DSP
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00:14 - Introduction to Digital Signal Processing (DSP)
04: 46 - Basic blocks of DSP
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DFT as a linear transformation method (Matrix method)
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How to calculate twiddle factor matrix in DFT
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00:13 - Relationship of DFT to Fourier Transform
02:10 - Relationship of DFT to Z Transform
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Properties of Discrete Fourier Transform (DFT)
00:47 - Periodicity property
01:27 - Linearity property
02:28 - circular time shift property with proof
05:20 - Circular time shift property based problem & solution
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Properties of Discrete Fourier Transform (DFT)
00:27 - Time reversal property
01:22 - Circular frequency property with proof
03:50 - Complex conjugate property with proof and solved problem
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Linear convolution
00:31 - Linear convolution equation
01:11 - Solved problem - Graphical method
10:51 - Solved problem - Matrix method
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Circular convolution
00:18 - Circular convolution Introduction
03:04 - Matrix method - Solved problem
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Circular convolution - Concentric Circle or Stockholm's Method
Solved probelm
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Linear convolution using circular convolution
Solved problem
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Filtering of long duration sequence - Overlap - save method
Solved problem
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Filtering of long duration sequence - Overlap - save method
Solved problem
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Filtering of long duration sequence - Overlap - Add method
Solved problem
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Filtering of long duration sequence - Overlap - Add method
Solved problem