{"id":559,"date":"2021-09-02T18:49:28","date_gmt":"2021-09-02T18:49:28","guid":{"rendered":"https:\/\/itgeeks.in\/home\/?p=559"},"modified":"2021-09-02T18:49:29","modified_gmt":"2021-09-02T18:49:29","slug":"2k6-ee-702-digital-signal-processing","status":"publish","type":"post","link":"https:\/\/itgeeks.in\/home\/?p=559","title":{"rendered":"2K6 EE 702 : DIGITAL SIGNAL PROCESSING"},"content":{"rendered":"\n

Module I (13 hours)<\/strong>
Discrete Signals \u2013 Signal Representation \u2013 Standard Discrete Time Signals \u2013 Classification of Discrete Time Signals \u2013 Basic Operations on Discrete Signals \u2013 Shifting, Time Reversal, Time Scaling, Scalar Multiplication, Signal Multiplier, Addition operation. Discrete Time System \u2013 Classifications- Static & Dynamic Systems, Time Variant & Time Invariant Systems, Causal & Non Causal Systems, Linear & Non Linear Systems, FIR and IIR Systems, Stable & Unstable Systems \u2013 Representation of arbitrary Sequence. Impulse Response and Convolution Sum, Convolution and Correlation of two Sequences – Inverse System – de convolution. Analysis of LTI discrete systems \u2013 Solution of difference equations by direct method, natural response, forced response- Step response and determination of impulse response h(n) from second order difference equation.
Module II (12 hours)<\/strong>
Frequency domain representations \u2013 representations of Discrete time Fourier series(DTFS)- Discrete time Fourier transform(DTFT) and its properties \u2013 frequency response of LTI Discrete- time system – sampling \u2013 aliasing effect- sampling theorem- – Z transforms – inverse Z transforms – bilinear transformation. Representation of discrete Fourier series (DFS) – Discrete Fourier transforms (DFT) and its properties. Inverse Discrete Fourier transforms (IDFT) – linear convolution \u2013 circular convolution – linear convolution with circular convolution using DFT – overlap – add method – overlap – save method.
Module III (14 hours)<\/strong>
FFT – Radix2 DIT FFT algorithm – Radix2 DIF FFT algorithm – IDFT using FFT algorithmbutterfly structure – bit reversed order – in – place computations Structures for realization of IIR systems and FIR systems. Quantization noise \u2013 derivation for quantization noise power \u2013 Fixed point and binary floating point number representation \u2013 comparison \u2013 over flow error \u2013 truncation error \u2013DSP chips – architecture of fixed point DSP core (schematics only)
Module IV (13 hours)<\/strong>
Digital filter design techniques – design of IIR filters from analog filters – analog to digital transformation – backward – difference and forward – difference approximations – impulse invariant transformation – bilinear transformation – prewarping – analog butterworth function for various filters – design example – properties of FIR filters – design of FIR filters using windows – comparison of IIR and FIR filters – finite word length effect in DSP<\/p>\n\n\n\n

Text books<\/strong>
1. Oppenhiem A.V. & Schafer R.W., Discrete-Time Signal Processing, Prentice Hall of India<\/a>
2.\u00a0Mitra S.K., Digital Signal Processing – A Computer Based Approach, Tata McGraw Hill<\/a>
Reference books<\/strong>
1. Ziemer R.E., Tranter W.H., & Fannin D.R, Signals And Systems-Continuous And Discrete, Pearson Education<\/a>
2.\u00a0Proakins J.G. & Manolakins D.G., Digital Signal Processing-Principles Algorithms And Applications, Prentice Hall of India<\/a>
3. Rabiner L.R. & Gold B, Theory and Application of Digital Signal Processing, Prentice Hall Of India
4. Ifeachor E.C., & Jervis B.W., Digital Signal Processing-A Practical Approach, Addison Wesley
5. DSP Users Manual, Texas Instruments, TMS320C54*DSP
6. CPU And peripherals reference set Vol. 1, DSP solutions<\/p>\n\n\n\n

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Question Papers<\/a><\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

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