DSP & Applications in Medicine Friday, January 14th, 2011

SCHEME    2006            
SUBJECT NAME DSP & Applications in Medicine



UNIT - 1
DISCRETE FOURIER TRANSFORM: Introduction, definition of DFT, properties of DFT, circular convolution, linear convolution using DFT.
6 Hours

UNIT - 2
FAST FOURIER TRANSFORM: Introduction, decimation in time FFT algorithm, computational efficiency, decimation in frequency algorithm.
7 Hours

UNIT - 3
REALIZATION OF DIGITAL SYSTEMS:  Introduction, block diagram and signal flow graph, basis IIR filter structures (Direct forms I & II), cascade and parallel realizations, basic FIR filter structures (Direct I & II) and linear phase FIR structures
7 Hours

UNIT - 4
FIR FILTER DESIGN:  Introduction, different types of windows- rectangular, Bartlett, Hanning, Hamming, Black Mann, and Kaiser windows, design of FIR filters using above windows, frequency sampling design, comparison of IIR & FIR digital filters.
6 Hours
UNITS - 5 & 6
ANALOG FILTER DESIGN:  Introduction, Butterworth filters, Chebyshev filters, general filter forms.
DESIGN OF IIR DIGITAL FILTER:  Introduction of filters, design of IIR digital filter through analog filters, impulse invariant transformations, bilinear transformations, design of digital Butter worth & Chebyshev filters, frequency transformation.
12 Hours
UNIT - 7
ADAPTIVE NOISE CANCELING:  Introduction, principles of adaptive noise canceling, adaptive noise canceling with the LMS algorithm, biomedical applications- applications of the adaptive noise canceling method: to enhance ECG monitoring, to enhance fetal ECG for monitoring, to enhance electro gastric measurement.
7 Hours
UNIT - 8
ADAPTIVE LINE ENHANCER AND ZERO TRACKING METHODS:  The ALE method using the LMS algorithm, adaptive line enhancement of diastolic heart sounds, adaptive line enhancement of ventricular late potentials.  The zero tracking method based on the LMS algorithm, adaptive zero tracking of EEG signals for detecting epileptic patients, adaptive zero tracking of visual evoked potentials.
7 Hour

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