Digital Signal Processing with MATLAB(R) (25 hours)

This course mainly deals with using MATLAB(R) Signal Processing toolbox for Digital signal processing, analysis, visualization, and algorithm development. The training covers various topics such as windowing techniques, filter design, transforms, multi-rate signal processing etc.

COURSE CONTENT :
 Introduction to DSP(3 hours)
  • Introduction to DSP• Sampled data systems
  • Aliasing and antialiasing
  • Reconstruction
  • Practical limitations
  • Frequency & amplitude resolution
  • Quantization and timing errors
  • Correlation and convolution
  • Frequency analysis
  • Fourier transforms
  • Frequency ‘leakage’
  • Windowing
  • Multi-rate signal processing
 Transforms (2 hours)
  • Fourier Transform• Z – Transform
  • DCT Transform
  • Wavelet Transform
 Filters(5 hours) FIR Filter –• FIR filter basics

  • Analysis of FIR filters
  • Frequency & impulse responses
  • The window design method
  • Optimization design methods
  • Practical limitations of FIR filters

IIR Filter –

  • IIR filter basics
  • Analysis of FIR filters
  • Frequency & impulse responses
  • IIR filter design
  • Poles, zeroes and filter response
DSP with MATLAB(R)
(5 hours)
  • Introduction to DSP Toolbox• Signal processing functions in MATLAB(R) (conv, conv2, corrcoef, cov, cplxpair, deconv, fft, fft2, fftshift, filter2, freqspace, ifft, ifft2,unwrap)
  • Time domain analysis of a signal
  • Frequency domain analysis of a signal
Digital Filter Design in MATLAB(R)
(2 hours)
  • Discrete-Time Filters (Direct form I, Direct form II, lattice filters)• 1_D Median filtering
  • Butterworth filter design
  • Chebyshev Type I filter design (pass band ripple)
  • Chebyshev Type II filter design (stop band ripple)
  • Raised cosine FIR filter design
  • Recursive digital filter design
Analog Filter Design in MATLAB(R)
(2 hours)
  • Analog Lowpass Filter Prototypes• Analog Filter Transformation
  • Bi-linesr transformation
  • Impulse-invariant Methods
  • Stabilising a polynomial
  • Z-Transform partial fraction expansion
Window Design(2 hour)
  • Rectangular window• Hamming window
  • Hanning window
  • Bartlett window
  • Kaiser window etc
Transforms(2 hour)
  • Discrete fourier transform• Discrete cosine transform
  • Hilbert transform
  • Discrete wavelet transform
  • inverse transforms
Multi-rate Signal Processing(2 hours)
  • Decimation• Interpolation
  • Up-Sampling
  • Down-Sampling
  • Re-Sampling
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