Signals and Systems MCQ (Multiple Choice Questions)

Signals & Systems MCQ - Multiple Choice Questions and Answers

Our 1000+ Signals & Systems MCQs (Multiple Choice Questions and Answers) focuses on all chapters of Signals & Systems covering 100+ topics. You should practice these MCQs for 1 hour daily for 2-3 months. This way of systematic learning will prepare you easily for Signals & Systems exams, contests, online tests, quizzes, MCQ-tests, viva-voce, interviews, and certifications.

Signals & Systems Multiple Choice Questions Highlights

- 1000+ Multiple Choice Questions & Answers (MCQs) in Signals & Systems with a detailed explanation of every question.
- These MCQs cover theoretical concepts, true-false(T/F) statements, fill-in-the-blanks and match the following style statements.
- These MCQs also cover numericals as well as diagram oriented MCQs.
- These MCQs are organized chapterwise and each Chapter is futher organized topicwise.
- Every MCQ set focuses on a specific topic of a given Chapter in Signals & Systems Subject.

Who should Practice Signals & Systems MCQs?

– Students who are preparing for college tests and exams such as mid-term tests and semester tests on Signals & Systems.
- Students who are preparing for Online/Offline Tests/Contests in Signals & Systems.
– Students who wish to sharpen their knowledge of Signals & Systems Subject.
- Anyone preparing for Aptitude test in Signals & Systems.
- Anyone preparing for interviews (campus/off-campus interviews, walk-in interview and company interviews).
- Anyone preparing for entrance examinations and other competitive examinations.
- All - Experienced, Freshers and College / School Students.

Signals & Systems Chapters

Here's the list of chapters on the "Signals & Systems" subject covering 100+ topics. You can practice the MCQs chapter by chapter starting from the 1st chapter or you can jump to any chapter of your choice.

  1. Signals and Systems Basics
  2. Time-Domain Analysis of CT Systems
  3. Time Domain Representation for LTI Systems
  4. Linear Algebra Overview
  5. Fourier Series
  6. Hilbert Spaces and Orthogonal Expansions
  7. Fourier Analysis on Complex Spaces
  8. Convergence
  9. Fourier Transform
  10. Sampling Theorem
  11. Laplace Transform and System Design
  12. Z-Transform and Digital Filtering
  13. Signal Transmission Through Linear Systems

advertisement
advertisement

3. Time Domain Representation for LTI Systems

The section contains MCQs on convolution and properties of impulse response representation for lti systems.

  • Convolution : Impulse Response Representation for LTI Systems – 1
  • Convolution : Impulse Response Representation for LTI Systems – 2
  • Properties of the Impulse Response Representation for LTI Systems
  • 4. Linear Algebra Overview

    The section contains multiple choice quesions and answers on linear algebra basics, vector basics, eigen vectors and functions of lti systems, matrix diagonalization and eigen values.

  • Basics of Linear Algebra
  • Eigenvalues
  • Vector Basics
  • Eigen vectors
  • Matrix diagonalization
  • Eigenfunctions of LTI systems
  • 5. Fourier Series

    The section contains questions and answers on periodic signals, fourier series, fourier coefficients, fourier series properties, lti systems, trigonometric fourier series, average power, power and energy signals, exponential fourier series, symmetry properties of fourier series, dirichlet conditions, gibbs phenomena, circular convolution properties and lti systems.

  • Periodic Signals – 1
  • Periodic Signals – 2
  • Fourier Series
  • Fourier Series & Coefficients – 1
  • Fourier Series & Coefficients – 2
  • Miscellaneous Examples on Fourier Series
  • Fourier Series Properties – 1
  • Fourier Series Properties – 2
  • Fourier Series and LTI Systems
  • Symmetry Properties of the Fourier Series
  • Dirichlet’s Conditions
  • Gibb’s Phenomena, Convergence of Fourier Series
  • Trigonometric Fourier Series
  • Average Power and Energy of a Signal
  • Power and Energy Signals
  • Exponential Fourier Series and Fourier Transforms
  • Circular Convolution Property of the Fourier Series
  • 6. Hilbert Spaces and Orthogonal Expansions

    The section contains MCQs on vector spaces, norms, inner products, hilbert spaces, cauchy schwarz inequality, basis types, orthonormal basis expansions, function space, haar wavelet basis, plancharel theorems and hilbert space projections.

  • Vector Spaces
  • Norms
  • Inner Products
  • Hilbert Spaces
  • Cauchy Schwarz Inequality
  • Common Hilbert Spaces
  • Types of Basis
  • Orthonormal Basis Expansions
  • Function Space
  • Haar Wavelet Basis
  • Orthonormal Bases in Real and Complex Spaces
  • Plancharel and Parseval’s Theorems
  • Approximation and Projections in Hilbert Space
  • 7. Fourier Analysis on Complex Spaces

    The section contains multiple choice questions and answers on fourier analysis and also in complex spaces, matrix equation for dtfs, fourier analysis using circuits, periodic extensions to dtfs, circular shifts, circular convolution, dft, fast fourier transform and its derivation.

    advertisement
  • Fourier Analysis
  • Fourier Series Analysis using Circuits
  • Fourier Analysis in Complex Spaces
  • Matrix Equation for the DTFS
  • Periodic Extension to DTFS
  • Circular Shifts
  • Circular Convolution and the DFT
  • DFT: Discrete Fourier Transform
  • Fast Fourier Transform
  • Derivation of the FFT
  • 8. Convergence

    The section contains questions and answers on convergence of sequences and vectors, uniform convergence of function sequences.

  • Convergence of sequences
  • Convergence of vectors
  • Uniform convergence of Function Sequences
  • 9. Fourier Transform

    The section contains MCQs on fourier transforms and its properties, inverse fourier transform, discrete fourier transformation, common and discrete time fourier transforms, dtft properties, dtft pair, dtft examples, ctft and its properties.

  • Fourier Transforms
  • Properties of Fourier Transforms
  • Inverse Fourier Transform
  • Discrete Fourier Transform
  • Common Fourier Transforms
  • Discrete-Time Fourier Transform
  • DTFT Properties
  • Discrete Fourier Transformation
  • DTFT Pair
  • DTFT Examples
  • CTFT
  • Properties of the CTFT
  • advertisement

    10. Sampling Theorem

    The section contains multiple choice questions and answers on sampling, reconstruction, nyquist theorem, discrete time processing of continous time signals, aliasing and anti-aliasing filters.

  • Sampling
  • Reconstruction
  • Nyquist Theorem
  • Aliasing
  • Anti-Aliasing Filters
  • Discrete Time Processng of Continuous Time Signals
  • 11. Laplace Transform and System Design

    The section contains questions and answers on laplace transform and its properties, bilateral laplace transform, common laplace transforms, convergence region, roc properties, systems characterization and nature, inverse laplace transform, poles and zeros.

  • The Laplace Transform
  • Properties of the Laplace Transform
  • Common Laplace Transforms – 1
  • Common Laplace Transforms – 2
  • Region of Convergence
  • Properties of ROC
  • Inverse Laplace Transform
  • Characterization and Nature of Systems
  • The Bilateral Laplace Transform
  • Poles and Zeros
  • 12. Z-Transform and Digital Filtering

    The section contains MCQs on z-transform and its properties, common and inverse z-transforms, rational functions, difference equations, zero plots on the z-plane, filter designs, bode plots, filters types, feedback systems, state space model and differential equations.

  • The Z-Transform
  • Properties of Z-Transforms – 1
  • Properties of Z-Transforms – 2
  • Inverse Z-Transform
  • Rational Functions
  • Difference Equations
  • Understanding Pole/Zero Plots on the Z-Plane
  • Common Z-Transforms
  • Filter Design using the Pole Zero Plot of a Z-Transform
  • Bode Plots
  • Types of Filters
  • Feedback Systems
  • State Space Model
  • Solving Differential Equations
  • 13. Signal Transmission Through Linear Systems

    The section contains multiple choice questions and answers on convolution concept, ideal lpf, hpf, bpf and bsf characteristics.

  • Ideal LPF, HPF, BPF and BSF Characteristics
  • Concept of Convolution
  • If you would like to learn "Signals & Systems" thoroughly, you should attempt to work on the complete set of 1000+ MCQs - multiple choice questions and answers mentioned above. It will immensely help anyone trying to crack an exam or an interview.

    Wish you the best in your endeavor to learn and master Signals & Systems!

    advertisement
    Manish Bhojasia - Founder & CTO at Sanfoundry
    Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He lives in Bangalore, and focuses on development of Linux Kernel, SAN Technologies, Advanced C, Data Structures & Alogrithms. Stay connected with him at LinkedIn.

    Subscribe to his free Masterclasses at Youtube & discussions at Telegram SanfoundryClasses.