PROGRAMME:  APPLIED ELECTRONICS & INSTRUMENTATION                               

DEGREE: BTECH

COURSE: SIGNALS & SYSTEMS

SEMESTER:    4            CREDITS: 4

COURSE CODE:  AI 010 403                                        REGULATION: 2012

COURSE TYPE: CORE

COURSE AREA/DOMAIN:

ELECTRONICS

CONTACT HOURS: 2+2 (Tutorial) Hours/Week.

CORRESPONDING LAB COURSE CODE (IF ANY): AI 010 708

LAB COURSE NAME: DSP Lab

UNIT

DETAILS

HOURS

I

Classification of signals: Continuous time and Discrete time,   Even and Odd ,   Periodic and Non-periodic , Energy and Power – Basic operations on signals: Operations performed on the dependent variable ,  operations on the independent variable: Shifting  , Scaling – Elementary Discrete time and Continuous time signals: Exponential , Sinusoidal , Step , Impulse , Ramp – Systems:  Properties of Systems: Stability, Memory, Causality, Invertibility, Time invariance, Linearity – LTI Systems: Representation of Signals in terms of impulses – Impulse response – Convolution sum and Convolution integral – Cascade and Parallel interconnections – Memory, Invertibility, Causality and Stability of LTI systems – Step response of LTI systems – Systems described by differential and difference equations (solution by conventional methods not required)

13

II

Fourier analysis for continuous time signals and systems: Representation of periodic signals: Continuous Time Fourier Series – convergence of Fourier series – Gibbs phenomenon – Representation of aperiodic signals: Continuous Time Fourier Transform – The Fourier Transform for periodic signals – Properties of Fourier representations – Frequency Response of systems characterized by linear constant coefficient differential equations

12

III

Fourier analysis for discrete time signals and systems: : Representation of periodic signals: Discrete Time Fourier Series  – Representation of aperiodic  signals: Discrete Time Fourier Transform – The Fourier Transform for periodic signals – Properties of Fourier representations – Frequency Response of systems characterized by linear constant coefficient difference equations

12

IV

Filtering: Frequency domain characteristics of ideal filters – Time domain characteristics of ideal LPF – Non-ideal filters – First and Second order filters described by differential and difference equations – Approximating functions: Butterworth, Chebyshev and elliptic filters (Magnitude response only) – Sampling: The sampling theorem – Reconstruction of a signal from its samples using interpolation – Aliasing

9

V

Bilateral Laplace Transform – ROC – Inverse – Geometric evaluation of the Fourier transform from pole-zero plot – Analysis and characterization of LTI systems using Laplace Transform – The Z Transform – ROC – Inverse – Geometric evaluation of the Fourier Transform from pole-zero plot – Properties of Z transform - Analysis and characterization of LTI systems using Z-Transform

13

TOTAL HOURS

59