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Course Co-ordinated by IIT Kanpur
Prof. Govind Sharma
IIT Kanpur


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Mathematics 3 (Web Course)


  1. Signals and signal processing

1.1 Characterization and classification of signals
1.2 Typical signal processing operations
1.3 Typical signal processing applications
1.4 Advantages of digital signal processing

  2. Time domain representations of signals and systems

2.1 Discrete time signals
2.2 Operations on sequences
2.3 Discrete time systems
2.4 Linear time invariant discrete time systems
2.5 Characterization of LTI systems
   3. Transform domain representation of signals and systems
3.1 The discrete time Fourier transform
3.2 The frequency response
3.3 The transfer function
3.4 Discrete Fourier series
3.5 Discrete Fourier transform
3.6 Computation of DFT
3.7 Linear convolution using DFT
3.8 The z-transform
3.9 The region of convergence of z-transform
   4. Structures for discrete time systems
4.1 Block diagram and signal flow representation of constant coefficient
      linear difference equation.
4.2 Basic structures for IIR systems
4.3 Basic structures for FIR systems
4.4 Lattice structures
4.5 Effects of coefficient quantization
4.6 Effect of roundoff noise in digital filters
4.7 Zero-input limit cycles
   5. Filter design techniques
5.1 Design of discrete time IIR filters from continuous time filters
5.2 Design of FIR filters by windowing
5.3 Optimum approximation of FIR filters
5.4 Linear phase filters
   6. Sampling of continuous time signals
6.1 Periodic sampling
6.2 Frequency domain representation of sampling
6.3 Reconstruction of bandlimited signal from its samples
6.4 Discrete time processing of continuous time signals
6.5 Continuous time processing of discrete time signals
6.6 Changing the sampling rate using discrete time processing
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