Electronics

Electronics is the science of how to control electric energy, energy in which the electrons have a fundamental role.electronics is widely used in information processing, telecommunication, and signal processing. The ability of electronic devices to act as switches makes digital information processing possible.

Wireless Communications

wireless communication include flexibility, cost effectiveness, constant connectivity, convenience and enhanced efficiency. These benefits make wireless communication quite attractive to businesses, government organizations and people in general.

VLSI technology

VLSI Design contains computer-aided design, design analysis, design implementation, simulation and testing.Hence there is tremendous scope and growth for those who choose VLSI design and embedded systems as a career.

Digital Signal Processing

Digital Signal Processing is one of the most powerful technologies that will shape science and engineering in the twenty-first century.DSP is the science of using computers to understand these types of data. This includes a wide variety of goals: filtering, speech recognition, image enhancement, data compression, neural networks, and much more.

Embedded Systems

Embedded systems is growing continuously. Exponentially increasing computing power, ubiquitous connectivity and convergence of technology have resulted in hardware/software systems being embedded within everyday products and places. Already today 90% of computing devices are in Embedded Systems and not in PCs. The growth rate in embedded systems is more than 10% per annum and it is forecasted there will be over 40 billion devices worldwide by 2020.

Signals & Systems Written Notes

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2.        Classification of Signals
4.       Fourier series
5.       Fourier Transform
6.      Laplace transform
9.      Z Transform

The above Notes Covers the below Topics:

UNIT-I: Signal Analysis and Fourier Series

Signal Analysis: Analogy between Vectors and Signals, Orthogonal Signal Space, Signal approximation using Orthogonal functions, Mean Square Error, Closed or complete set of Orthogonal functions, Orthogonality in Complex functions, Exponential and Sinusoidal signals, Concepts of Impulse function, Unit Step function, Signum function.
Fourier Series: Representation of Fourier series, Continuous time periodic signals, Properties of Fourier Series, Dirichlet’s conditions, Trigonometric Fourier Series and Exponential Fourier Series, Complex Fourier spectrum.


UNIT-II: Fourier Transforms and Sampling
Fourier Transforms: Deriving Fourier Transform from Fourier Series, Fourier Transform of arbitrary signal, Fourier Transform of standard signals, Fourier Transform of Periodic Signals, Properties of Fourier Transform, Fourier Transforms involving Impulse function and Signum function, Introduction to Hilbert Transform.

Sampling: Sampling theorem – Graphical and analytical proof for Band Limited Signals, Types of Sampling - Impulse Sampling, Natural and Flat-top Sampling, Reconstruction of signal from its samples, Effect of under sampling – Aliasing, Introduction to Band Pass sampling.


 UNIT-III:

Signal Transmission Through Linear Systems: Linear System, Impulse response, Response of a Linear System, Linear Time variant(LTI)System, Linear Time Variant(LTV) System, Transfer function of a LTI system, Filter characteristics of Linear Systems, Distortion less transmission through a system, Signal bandwidth, System bandwidth, Ideal LPF, HPF and BPF characteristics, Causality and Paley-Wiener criterion for physical realization, Relationship between Bandwidth a d Rise time.


 UNIT-IV:

Convolution and Correlation of Signals: Concept of convolution in Time domain and Frequency domain, Graphical representation of Convolution, Convolution property of Fourier Transforms, Cross Correlation and Auto Correlation of functions, Properties of Correlation function, Energy density spectrum, Parseval’s Theorem, Power density spectrum, Relation between Auto Correlation function and Energy/Power spectral density function, Relation between Convolution and Correlation, Detection of periodic signals in the presence of Noise by Correlation, Extraction of signal from noise by filtering.


UNIT-V: Laplace Transforms and Z-Transforms
Laplace Transforms: Review of Laplace Transforms (L.T), Partial fraction expansion, Inverse Laplace Transform, Concept of Region of Convergence (ROC) for Laplace Transforms, Constraints on ROC for various classes of signals, Properties of L.T, Relation between L.T and F.T of a signal, Laplace Transform of certain signals using waveform synthesis.

Z–Transforms: Fundamental difference between Continuous and Discrete time signals, Discrete time signal representation using Complex exponential and Sinusoidal components, Periodicity of Discrete time signal using complex exponential signal, Concept of Z- Transform of a Discrete Sequence, Distinction between Laplace, Fourier and Z Transforms, Region of Convergence in Z-Transform, Constraints on ROC for various classes of signals, Inverse Z-transform, Properties of Z-transforms.

Suggested Books:
  1. Signals and Systems by Alan V. Oppenheim, Alan S. Wilsky
  2. Signals and Systems by A Anand Kumar
  3. Signals, Systems and Communication by B.P. Lathi
  4. Signalsand Systems using MATLAB by Luis F. Chaparro
      

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