NOC:Discrete Time Signal Processing - Study24x7
NOC:Discrete Time Signal Processing

NOC:Discrete Time Signal Processing

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Description

Discrete time views values of variables as occurring at distinct, separate "points in time", or equivalently as being unchanged throughout each non-zero region of time ("time period")—that is, time is viewed as a discrete variable. Thus a non-time variable jumps from one value to another as time moves from one time period to the next. This view of time corresponds to a digital clock that gives a fixed reading of 10:37 for a while, and then jumps to a new fixed reading of 10:38, etc. In this framework, each variable of interest is measured once at each time period. The number of measurements between any two time periods is finite. Measurements are typically made at sequential integer values of the variable "time".

Includes

  • NOC:Discrete Time Signal Processing Total 8 Modules
  • NOC:Discrete Time Signal Processing 40 Videos
  • NOC:Discrete Time Signal Processing Downloadable on mobile
  • NOC:Discrete Time Signal Processing Published on 26 June, 2019

Course Content

module :1

NOC:Discrete Time Signal Processing
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    Lecture 01: Introduction

    31m <?php echo  $alt; ?>
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    Lecture 02: Discrete Time Signals and Systems

    29m <?php echo  $alt; ?>
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    Lecture 03: Linear, Shift Invariant Systems?

    34m <?php echo  $alt; ?>
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    Lecture 04 : Properties of Discrete Convolution Causal and Stable Systems?

    32m <?php echo  $alt; ?>
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    Lecture 05: Graphical Evaluation of Discrete Convolutions

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Module : 2

NOC:Discrete Time Signal Processing
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    Lecture 06: Discrete Time Fourier Transform?

    31m <?php echo  $alt; ?>
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    Lecture 07: Properties of DTFT

    29m <?php echo  $alt; ?>
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    Lecture 08: Dirac Comb and Sampling Analog Signals?

    29m <?php echo  $alt; ?>
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    Lecture 09: Relation between DTFT and Analog Fourier Transform?

    27m <?php echo  $alt; ?>
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    Lecture 10: Nyquist Interpolation Formula

    27m <?php echo  $alt; ?>

Module : 3

NOC:Discrete Time Signal Processing
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    Lecture 11: Rational Systems

    26m <?php echo  $alt; ?>
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    Lecture 12: Properties of Rational Systems

    32m <?php echo  $alt; ?>
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    Lecture 13: Introduction to Z-transform

    28m <?php echo  $alt; ?>
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    Lecture 14: Properties of Z-transform

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    Lecture 15: Properties of z-transform

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Module : 4

NOC:Discrete Time Signal Processing
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    Lecture 16: Inverse z-transform

    42m <?php echo  $alt; ?>
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    Lecture 17:Introduction to DFT

    34m <?php echo  $alt; ?>
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    Lecture 18: Properties of DFT

    33m <?php echo  $alt; ?>
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    Lecture 19:Introduction to Interpretation of Circular Convolution

    32m <?php echo  $alt; ?>
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    Lecture 20: Graphically Interpretation of Circular Convolution

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Module : 5

NOC:Discrete Time Signal Processing
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    Lecture 21: Zero Padding and Linear convolution Via DFT

    37m <?php echo  $alt; ?>
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    Lecture 22: Decimation and DFT of Decimated Sequences

    28m <?php echo  $alt; ?>
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    Lecture 23: Expension and Interpolation of Sequences

    29m <?php echo  $alt; ?>
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    Lecture 24: Factor-of-M Polyphase Decomposition of Sequences

    38m <?php echo  $alt; ?>
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    Lecture 25: Nobel Identifies

    35m <?php echo  $alt; ?>

Module : 6

NOC:Discrete Time Signal Processing
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    Lecture 26: Efficient Decimator and Interpolator Structure

    35m <?php echo  $alt; ?>
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    Lecture 27: Linear Phase Filters

    31m <?php echo  $alt; ?>
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    Lecture 28: Properties of Linear Phase Filters

    33m <?php echo  $alt; ?>
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    Lecture 29: Structures for IIR Filters

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    Lecture 30: Structures for FIR Filters

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Module : 7

NOC:Discrete Time Signal Processing
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    Lecture 31: Analog LTI Systems, Fourier and Laplace Transforms

    32m <?php echo  $alt; ?>
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    Lecture 32: Pole, Zero and Stability of of Analog Filters

    29m <?php echo  $alt; ?>
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    Lecture 33: Analog Filter Design Example Butterworth Lowpass Filter

    30m <?php echo  $alt; ?>
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    Lecture 34: IIR Filter Design by Implus Invariance Method

    32m <?php echo  $alt; ?>
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    Lecture 35: Design Filter Design from Analog Proptotype Filters by s - z Transformations

    29m <?php echo  $alt; ?>

Module : 8

NOC:Discrete Time Signal Processing
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    Lecture 36: Bilinear Transformation

    29m <?php echo  $alt; ?>
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    Lecture 37: FIR Filter Design by Window

    32m <?php echo  $alt; ?>
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    Lecture 38: FFT: Decimation in Time

    28m <?php echo  $alt; ?>
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    Lecture 39: Complexity Analysis of FFT

    29m <?php echo  $alt; ?>
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    Lecture 40: Bit Reversal and FFT

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