Electronic Communications: A Systems Approach Beasley | Hymer | Miller Copyright © 2014 by Pearson Education, Inc. All Rights Reserved Information and.

Slides:

Advertisements

Similar presentations

DCSP-3: Fourier Transform (continuous time) Jianfeng Feng

Advertisements

DCSP-3: Fourier Transform Jianfeng Feng Department of Computer Science Warwick Univ., UK

Principles of Electronic Communication Systems Second Edition Louis Frenzel © 2002 The McGraw-Hill Companies.

Fourier Series 主講者：虞台文.

3.1 Chapter 3 Data and Signals Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

Copyright ©2011 by Pearson Education, Inc. Upper Saddle River, New Jersey All rights reserved. Introduction to Engineering Experimentation, Third.

Chapter 3 Data and Signals

Signals The main function of the physical layer is moving information in the form of electromagnetic signals across a transmission media. Information can.

Physics 1251 The Science and Technology of Musical Sound Unit 1 Session 8 Harmonic Series Unit 1 Session 8 Harmonic Series.

3.1 Chapter 3 Data and Signals Computer Communication & Networks.

Chi-Cheng Lin, Winona State University CS412 Introduction to Computer Networking & Telecommunication Theoretical Basis of Data Communication.

Modern Electronic Communication 9th edition Jeffrey S. Beasley and Gary M. Miller Copyright ©2008 by Pearson Education, Inc. Upper Saddle River, New Jersey.

Chapter 2 Data and Signals

Note To be transmitted, data must be transformed to electromagnetic signals.

Modern Electronic Communication 9th edition Jeffrey S. Beasley and Gary M. Miller Copyright ©2008 by Pearson Education, Inc. Upper Saddle River, New Jersey.

1 Lecture 27 Physical Layer (Data and Signals) University of Nevada – Reno Computer Science & Engineering Department Fall 2010 CPE 400 / 600 Computer Communication.

Fourier Series.

Signals Processing Second Meeting. Fourier's theorem: Analysis Fourier analysis is the process of analyzing periodic non-sinusoidal waveforms in order.

3.1 Chapter 3 Data and Signals Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

Chapter 18 Fourier Circuit Analysis

Waveform and Spectrum A visual Fourier Analysis. String with fixed ends.

Time and Frequency Representation

Principles of Electronic Communication Systems

2 Amplitude Modulation.

CH#3 Fourier Series and Transform

Digital Communication Techniques

Chapter 25 Nonsinusoidal Waveforms. 2 Waveforms Used in electronics except for sinusoidal Any periodic waveform may be expressed as –Sum of a series of.

Where we’re going Speed, Storage Issues Frequency Space.

Modern Electronic Communication 9th edition Jeffrey S. Beasley and Gary M. Miller Copyright ©2008 by Pearson Education, Inc. Upper Saddle River, New Jersey.

Lecture 1 Signals in the Time and Frequency Domains

Fourier (1) Hany Ferdinando Dept. of Electrical Eng. Petra Christian University.

5 Transmitters.

Modern Electronic Communication 9th edition Jeffrey S. Beasley and Gary M. Miller Copyright ©2008 by Pearson Education, Inc. Upper Saddle River, New Jersey.

Fourier Concepts ES3 © 2001 KEDMI Scientific Computing. All Rights Reserved. Square wave example: V(t)= 4/  sin(t) + 4/3  sin(3t) + 4/5  sin(5t) +

INTRODUCTION TO ANALOG COMMUNICATION (Chapter 1) elctronicsa2z.com.

Fourier series. The frequency domain It is sometimes preferable to work in the frequency domain rather than time –Some mathematical operations are easier.

Fundamentals of Electric Circuits Chapter 17

Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 1 Chapter 19.

Chapter 3 Data and Signals

EE210 Digital Electronics Class Lecture 2 March 20, 2008.

12 Transmission Lines.

1 Principles of Electronic Communication Systems Third Edition Louis E. Frenzel, Jr. © 2008 The McGraw-Hill Companies.

ELECTRONIC COMMUNICATIONS A SYSTEMS APPROACH CHAPTER Copyright © 2014 by Pearson Education, Inc. All Rights Reserved Electronic Communications: A Systems.

ELECTRONIC COMMUNICATIONS A SYSTEMS APPROACH CHAPTER Copyright © 2014 by Pearson Education, Inc. All Rights Reserved Electronic Communications: A Systems.

ELECTRONIC COMMUNICATIONS A SYSTEMS APPROACH CHAPTER Copyright © 2014 by Pearson Education, Inc. All Rights Reserved Electronic Communications: A Systems.

Question 1 Find the following using dB and dBm transformations: a) Power in dB for 22 W b) Power in dBm for 4.8 W c) Power in W for 25 dB.

By Ya Bao oct 1 Fourier Series Fourier series: how to get the spectrum of a periodic signal. Fourier transform: how.

Complex Auditory Stimuli

1 Outline Analog and Digital Data Analog and Digital Signals Amplitude Modulation (AM) Frequency Modulation (FM)

12/2/2015 Fourier Series - Supplemental Notes A Fourier series is a sum of sine and cosine harmonic functions that approximates a repetitive (periodic)

McGraw-Hill©The McGraw-Hill Companies, Inc., 2004 Physical Layer PART II.

CH#3 Fourier Series and Transform

CS434/534: Mobile Computing and Wireless Networks Y. Richard Yang 08/30/2012.

EET260 Frequency Modulation. Modulation A sine wave carrier can be modulated by varying its amplitude, frequency, or phase shift. In AM, the amplitude.

Modern Electronic Communication 9th edition Jeffrey S. Beasley and Gary M. Miller Copyright ©2008 by Pearson Education, Inc. Upper Saddle River, New Jersey.

Prof. Nizamettin AYDIN Advanced Digital Signal Processing 1.

The Spectrum n Jean Baptiste Fourier ( ) discovered a fundamental tenet of wave theory.

1 EE2003 Circuit Theory Chapter 17 The Fourier Series Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

EEE 332 COMMUNICATION Fourier Series Text book: Louis E. Frenzel. Jr. Principles of Electronic Communication Systems, Third Ed. Mc Graw Hill.

Spectrum Analyzer. SPECTRUM ANALYZERS The problems associated with non-real-time analysis in the frequency domain can be eliminated by using a spectrum.

ELECTRIC CIRCUITS EIGHTH EDITION JAMES W. NILSSON & SUSAN A. RIEDEL.

CH#3 Fourier Series and Transform 1 st semester King Saud University College of Applied studies and Community Service 1301CT By: Nour Alhariqi.

McGraw-Hill © 2008 The McGraw-Hill Companies, Inc. All rights reserved. Principles of Electronic Communication Systems.

MODULE 2: Circuits, Signals and the Analog Discovery Board SUMMER CHALLENGE Electrical Engineering: Smart Lighting Michael Rahaim, PhD Candidate Multimedia.

Figure Hz sine wave to be sampled.

The Inverse Sine, Cosine, and Tangent Functions

EE210 Digital Electronics Class Lecture 2 September 03, 2008

Graphs of the Sine and Cosine Functions

C H A P T E R 21 Fourier Series.

3.1 Chapter 3 Data and Signals Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display.

Presentation transcript:

Electronic Communications: A Systems Approach Beasley | Hymer | Miller Copyright © 2014 by Pearson Education, Inc. All Rights Reserved Information and Bandwidth Bandwidth  Defines frequency range over which a circuit or system operates.  Greater the bandwidth, greater the amount of information transferred.  Hartley’s law Information transmitted directly proportional to product of bandwidth used and time of transmission

Electronic Communications: A Systems Approach Beasley | Hymer | Miller Copyright © 2014 by Pearson Education, Inc. All Rights Reserved Information and Bandwidth Bandwidth  Radio-frequency spectrum is a scarce and valuable public resource.

Electronic Communications: A Systems Approach Beasley | Hymer | Miller Copyright © 2014 by Pearson Education, Inc. All Rights Reserved Information and Bandwidth Understanding Frequency Spectra  The locations on spectrum of all frequencies produced as the result of modulation are what determine bandwidth of the modulated signal.  Fourier: developed means to break down periodic waveforms into a series of sine and/or cosine waves at multiples of the fundamental frequency.

Electronic Communications: A Systems Approach Beasley | Hymer | Miller Copyright © 2014 by Pearson Education, Inc. All Rights Reserved Information and Bandwidth Time- and Frequency-Domain Representations  Time domain Waveform amplitude as a function of time  Oscilloscope is a time-domain representation.

Electronic Communications: A Systems Approach Beasley | Hymer | Miller Copyright © 2014 by Pearson Education, Inc. All Rights Reserved Table 1-3 Fourier Expressions for Selected Periodic Waveforms, f = 1/T, 2πf = ω

Electronic Communications: A Systems Approach Beasley | Hymer | Miller Copyright © 2014 by Pearson Education, Inc. All Rights Reserved Information and Bandwidth Time- and Frequency-Domain Representations  Frequency domain Amplitude viewed as function of frequency rather than of time  Spectrum analyze Signals in frequency domain

Electronic Communications: A Systems Approach Beasley | Hymer | Miller Copyright © 2014 by Pearson Education, Inc. All Rights Reserved Figure 1-5 (a) Fundamental frequency (sin ωt); (b) the addition of the first and third harmonics (sin ωt + 1/3 sin 3 ωt); (c) addition of the first, third, and fifth harmonics (sin ωt + 1/3 sin 3 ωt + 1/5 sin 5 ωt); (d) addition of the first 13 odd harmonics; (e) addition of the first 51 harmonics.

Electronic Communications: A Systems Approach Beasley | Hymer | Miller Copyright © 2014 by Pearson Education, Inc. All Rights Reserved Information and Bandwidth The Fast Fourier Transform  Conversion from time to frequency domain approximated with fast Fourier transform (FFT).  Algorithm suited to computer-based implementation.  It allows for large number of calculations to be reduced to a manageable number through elimination of redundancies.

Electronic Communications: A Systems Approach Beasley | Hymer | Miller Copyright © 2014 by Pearson Education, Inc. All Rights Reserved Figure 1-7 A 1-kHz square wave and its FFT representation.