Scribd
Upload
81 views15 pages

Introduction To Signal and Systems: S. Arosh

This document provides an introduction to signals and systems. It defines various types of signals, such as continuous/discrete, analog/digital, real/complex, deterministic/random, even/odd, periodic/non-periodic, energy/power. It also defines basic continuous-time and discrete signals like the unit step, unit impulse, complex exponentials, and sinusoidal signals. Finally, it covers systems and classifications of systems, including linear/nonlinear, time-invariant/time-varying, causal/non-causal, and stable systems. Fourier series are introduced as a way to represent any periodic signal as a sum of sinusoids.

Uploaded by

Backup G
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PPTX, PDF, TXT or read online on Scribd
81 views15 pages

Introduction To Signal and Systems: S. Arosh

This document provides an introduction to signals and systems. It defines various types of signals, such as continuous/discrete, analog/digital, real/complex, deterministic/random, even/odd, periodic/non-periodic, energy/power. It also defines basic continuous-time and discrete signals like the unit step, unit impulse, complex exponentials, and sinusoidal signals. Finally, it covers systems and classifications of systems, including linear/nonlinear, time-invariant/time-varying, causal/non-causal, and stable systems. Fourier series are introduced as a way to represent any periodic signal as a sum of sinusoids.

Uploaded by

Backup G
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PPTX, PDF, TXT or read online on Scribd
You are on page 1/ 15

Introduction to signal and

systems
S. Arosh
Types of Signals
 continuous time and discrete time signal
 Analog and Digital Signals
 Real and Complex Signals
 Deterministic and Random Signals
 Even and Odd Signals
 Periodic and Non-periodic Signals
 Energy and Power Signals
A signal is referred to as an even if it
Types of Signals is identical to its time-reversed
counterparts; x(t) = x(-t). Odd Signal:
A signal is odd if x(t) = -x(-t). An odd
 continuous time and discrete time signal signal must be 0 at t=0, in other
words, odd signal passes the origin.
 Analog and Digital Signals:
 Real and Complex Signals A signal which repeats itself after a
specific interval of time is
 Deterministic and Random Signals called periodic signal. ... A signals that
 Even and Odd Signals repeats its pattern over a period is
called periodic signal, A signal that does
 Periodic and Nonperiodic Signals not repeats its pattern over a period is
 Energy and Power Signals called aperiodic signal or non periodic

A power signal is a signal that has


finite power for each point in time.
So if a signal is a power signal then
the value at each point should be
finite. An energy signal is one that
has finite energy. ... And if they are
truncated(limited in time) they are
also energy signals.
BASIC CONTINUOUS-TIME/DISCRETE SIGNALS
 The Unit Step Function
 The Unit Impulse Function
 Complex Exponential Signals
 Real Exponential Signals
 Sinusoidal Signals
SYSTEMS AND CLASSIFICATION OF SYSTEMS

 System Representation
 Continuous Time and Discrete-Time Systems
 Systems with Memory and without Memory
 Causal and Noncausal Systems
 Linear Systems and Nonlinear Systems
 Time-Invariant and Time-Varying Systems
 Linear Time-Invariant Systems
 Stable Systems/Feedback System
SYSTEMS AND CLASSIFICATION OF SYSTEMS

 System Representation
 Continuous Time and Discrete-Time Systems
 Systems with Memory and without Memory
 Causal and Noncausal Systems
 Linear Systems and Nonlinear Systems
 Time-Invariant and Time-Varying Systems
 Stable Systems/Feedback System
SYSTEMS AND CLASSIFICATION OF SYSTEMS

 System Representation
 Continuous Time and Discrete-Time Systems
 Systems with Memory and without Memory
 Causal and Non-causal Systems
 Linear Systems and Nonlinear Systems
 Time-Invariant and Time-Varying Systems
 Linear Time-Invariant Systems
 Stable Systems/Feedback System
Fourier Series
 Wave Analysis: The French mathematician Fourier found that any periodic waveform, that
is, a waveform that repeats itself after some time, can be expressed as a series of
harmonically related sinusoids, i.e., sinusoids whose frequencies are multiples of a
fundamental frequency (or first harmonic). For example, a series of sinusoids with
frequencies 1 MHz 2 MHz 3 MHz and so on, contains the fundamental frequency of 1
MHz , a second harmonic of 2 MHz, a third harmonic of 3 MHz, and so on. In general, any
periodic waveform can be expressed as
Fourier Series
Fourier Series
Fourier Series
Fourier Series
Fourier Series
Fourier Series

Fourier Series
Links
 Video Links
 https://www.youtube.com/watch?v=ds0cmAV-Yek&t=181s
 https://www.youtube.com/watch?v=r6sGWTCMz2k
 http://bilimneguzellan.net/fuyye-serisi/ [in Turkish, translate]

You might also like