B.E Jadavpur University Electrical Engineering - Digital Signal Processing (3rd Year First Semester) -2019 model question papers



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Posted Date: 08 Mar 2020      Posted By:: Shouvik Maj    Member Level: Silver  Points: 3 (₹ 3)

2019 B.E Electrical Engineering B.E Jadavpur University Electrical Engineering - Digital Signal Processing (3rd Year First Semester) -2019 Question paper



Course: B.E Electrical Engineering   University/board: Jadavpur University

Are you looking for the old question papers of Jadavpur University Computer Science & Engineering - Digital Signal Processing ? Here is the previous year question paper from Jadavpur University. This is the original question paper from the Electrical Engineering Department for Third year first semester exam conducted by Jadavpur University in year 2019. Feel free to download the question paper from here and use it to prepare for your upcoming exams.



{Scroll Below to get the PDF Attachment file of the Original Question Paper}

Exam Name- B.E Electrical Engineering Exam
3rd Year- 1st Semester

Subject- Digital Signal Processing

Total Time- Three Hours
Maximum Marks- 100

Syllabus

Analog Signal Processing versus Digital Sgnal Processing. Review of Sampling.
Aliasing. Frequency domain representation of uniformly-sampled signals. Anti-alias filter.
Power and energy sequences. Odd and even sequences.Causal, anticausal and twosided sequences. Periodic sequences. Time-domain operation on sequences- timescaling, time-reversal, time-shifting. Review of Z-transform and its properties. ROCs of
Z-transforms. Mapping between z-plane and s-plane. Discrete-Time Fourier Transform
and its properties. Parseval's formula. Discrete-time LTI systems, Z-transfer function.
Discrete-time convolution, its properties and interconnection of LTI systems. Recursive
and Non-recursive systems. Z-Transforms Of Causal Sequences & Time Domain
Behaviour. FIR and IIR systems. Ideal interpolation formula for reconstructing analog
signals from their samples. DAC employing zero-order hold. Image rejection postfiltering, compensated reconstruction filter. Design of IIR filters: Standard transformation
techniques- Impulse invariant transformation, Bilinear transformation, Mapping of
differentials, Matched z-transformation. Structures for IIR filters: Direct form, cascade
realization, parallel realization, transposed structures, ladder structure. Finite-wordlength
effects in digital IIR filters, limit cycles.
Introduction to Discrete Fourier transform (DFT): Fourier series for a periodic signal,
Fourier series for a periodic discrete sequence, discrete Fourier transform (DFT), inverse
discrete Fourier transform (IDFT). Properties of DFT: periodicity, symmetry. Computation
of DFT. Fast Fourier transform (FFT): radix-2 decimation in frequency in-place FFT
algorithm. Comparison of DFT and FFT. Applications of FFT.
FIR digital filters. Distortion less transmission of signal through a filter: linear phase
characteristic. Concepts of phase delay and group delay. Linear phase digital filter.
Properties of linear phase digital filter: periodicity, symmetry. Design of digital filter by
Fourier series method. Frequency response of digital filters, realization problems. Direct
realization of linear phase FIR digital filters, effect of truncation of impulse response,
circular complex convolution integral, Gibbs phenomenon. Common window functions
for linear phase FIR filter design: Bartlett, Hamming, Hann, Blackman. Frequency
domain characteristic of common window functions. Design of brick-wall type low pass,
high pass, band pass FIR digital filters. Design of linear phase FIR filters by the
frequency sampling method. Design of optimum equiripple linear phase FIR filters. FIR
digital filters for off-line analysis for one-dimensional (1-D) and two-dimensional (2-D)
data. 2-D finite impulse sequence of digital FIR filter.
Digital signal processors. Processor architecture: Von Neumann architecture, Harvard
architecture, modified Harvard architecture. TMS320C25 processor: architecture,
multiply/accumulate operation, benchmarks.
Introduction to image processing: gray image as a 2-D continuous function of space.
Image filtering: a 2-D filtering problem, FIR image filters for low pass and high pass
filtering. Contrast enhancement by histogram equalization.



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