CEN352, Dr. Ghulam Muhammad King Saud University

Slides:



Advertisements
Similar presentations
Analog to digital conversion
Advertisements

| Page Angelo Farina UNIPR | All Rights Reserved | Confidential Digital sound processing Convolution Digital Filters FFT.
Chapter 4 sampling of continous-time signals 4.5 changing the sampling rate using discrete-time processing 4.1 periodic sampling 4.2 discrete-time processing.
Symmetry and the DTFT If we know a few things about the symmetry properties of the DTFT, it can make life simpler. First, for a real-valued sequence x(n),
ECE 4371, Fall, 2014 Introduction to Telecommunication Engineering/Telecommunication Laboratory Zhu Han Department of Electrical and Computer Engineering.
Digital Coding of Analog Signal Prepared By: Amit Degada Teaching Assistant Electronics Engineering Department, Sardar Vallabhbhai National Institute of.
Motivation Application driven -- VoD, Information on Demand (WWW), education, telemedicine, videoconference, videophone Storage capacity Large capacity.
Sampling and quantization Seminary 2. Problem 2.1 Typical errors in reconstruction: Leaking and aliasing We have a transmission system with f s =8 kHz.
ADC AND DAC Sub-topics: Analog-to-Digital Converter -. Sampling
Quantization Prof. Siripong Potisuk.
Introduction to D/A and A/D conversion Professor: Dr. Miguel Alonso Jr.
Introduction to Data Conversion
Continuous-Time Signal Analysis: The Fourier Transform
Digital Signal Processing – Chapter 7
Data Acquisition. Data Acquisition System Analog Signal Signal Conditioner ADC Digital Processing Communication.
Sampling of Continuous-Time Signals
First semester King Saud University College of Applied studies and Community Service 1301CT.
Digital to Analogue Conversion Natural signals tend to be analogue Need to convert to digital.
Echivalarea sistemelor analogice cu sisteme digitale Prof.dr.ing. Ioan NAFORNITA.
DSP for Dummies aka How to turn this (actual raw sonar trace) Into this.. (filtered sonar data)
Signal ProcessingES & BM MUET1 Lecture 2. Signal ProcessingES & BM MUET2 This lecture Concept of Signal Processing Introduction to Signals Classification.
EE421, Fall 1998 Michigan Technological University Timothy J. Schulz 08-Sept, 98EE421, Lecture 11 Digital Signal Processing (DSP) Systems l Digital processing.
Chapter 5 Frequency Domain Analysis of Systems. Consider the following CT LTI system: absolutely integrable,Assumption: the impulse response h(t) is absolutely.
Sampling Theorems. Periodic Sampling Most signals are continuous in time. Example: voice, music, images ADC and DAC is needed to convert from continuous-time.
Professor: Dr. Miguel Alonso Jr.
Chapter #5 Pulse Modulation
CEN352 Digital Signal Processing Lecture No. 1 Department of Computer Engineering, College of Computer and Information Sciences, King Saud University,
Chapter 5 Frequency Domain Analysis of Systems. Consider the following CT LTI system: absolutely integrable,Assumption: the impulse response h(t) is absolutely.
1 Prof. Nizamettin AYDIN Advanced Digital Signal Processing.
Notice  HW problems for Z-transform at available on the course website  due this Friday (9/26/2014) 
Prof. Brian L. Evans Dept. of Electrical and Computer Engineering The University of Texas at Austin Lecture 4 EE 345S Real-Time.
CS Spring 2009 CS 414 – Multimedia Systems Design Lecture 3 – Digital Audio Representation Klara Nahrstedt Spring 2009.
Technological Educational Institute Of Crete Department Of Applied Informatics and Multimedia Neural Networks Laboratory Slide 1 FOURIER TRANSFORMATION.
Digital Signal Processing
Sampling of Continuous-Time Signals Quote of the Day Optimist: "The glass is half full." Pessimist: "The glass is half empty." Engineer: "That glass is.
Sampling and Aliasing.
Lecture 2 Analog to digital conversion & Basic discrete signals.
Continuous-time Signal Sampling
1 What is Multimedia? Multimedia can have a many definitions Multimedia means that computer information can be represented through media types: – Text.
Introduction to Data Conversion EE174 – SJSU Tan Nguyen.
Chapter 2 Ideal Sampling and Nyquist Theorem
Digital Signal Processing
Lifecycle from Sound to Digital to Sound. Characteristics of Sound Amplitude Wavelength (w) Frequency ( ) Timbre Hearing: [20Hz – 20KHz] Speech: [200Hz.
Lecture 1.4. Sampling. Kotelnikov-Nyquist Theorem.
Fourier Analysis Patrice Koehl Department of Biological Sciences National University of Singapore
Digital Signal Processing (7KS01)
Sampling and Aliasing Prof. Brian L. Evans
Chapter 3 Sampling.
Sampling and Quantization
Lecture Signals with limited frequency range
Signals and Systems Lecture 20
EE Audio Signals and Systems
I. Previously on IET.
Fundamentals Data.
لجنة الهندسة الكهربائية
Chapter 2 Signal Sampling and Quantization
Lecture 9: Sampling & PAM 1st semester By: Elham Sunbu.
Soutenance de thèse vendredi 24 novembre 2006, Lorient
لجنة الهندسة الكهربائية
Lecture 10 Digital to Analog (D-to-A) Conversion
Lecture 4 Sampling & Aliasing
Digital Control Systems Waseem Gulsher
Chapter 2 Ideal Sampling and Nyquist Theorem
Sampling and Quantization
CEN352, Dr. Ghulam Muhammad King Saud University
Chapter 3 Sampling.
Today's lecture System Implementation Discrete Time signals generation
Sampling and Aliasing.
ELEN E4810: Digital Signal Processing Topic 11: Continuous Signals
DIGITAL CONTROL SYSTEM WEEK 3 NUMERICAL APPROXIMATION
Presentation transcript:

CEN352, Dr. Ghulam Muhammad King Saud University Digital Signal Analog Signal Discrete-time Signal Continuous amplitude Continuous amplitude Continuous time Discrete time Discrete amplitude Digital Signal Discrete time CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Digital Signal – contd. Discrete-time Signal Analog Signal Digital Signal CEN352, Dr. Ghulam Muhammad King Saud University

DSP (Digital Signal Processing) A digital signal processing scheme Analog to Digital Converter Digital to Analog Converter To avoid aliasing for sampling To avoid aliasing for sampling Computer / microprocessor / micro controller/ etc. CEN352, Dr. Ghulam Muhammad King Saud University

Some Applications of DSP Noise removal from speech. Noisy Speech Clean Speech CEN352, Dr. Ghulam Muhammad King Saud University

Some Applications of DSP Signal spectral analysis. Time domain Frequency domain Single tone: 1000 Hz Double tone: 1000 Hz and 3000 Hz CEN352, Dr. Ghulam Muhammad King Saud University

Some Applications of DSP Noise removal from image. CEN352, Dr. Ghulam Muhammad King Saud University

Some Applications of DSP Image enhancement. CEN352, Dr. Ghulam Muhammad King Saud University

Summary Applications of DSP Speech recognition Speaker recognition Speech synthesis Speech enhancement Speech coding Digital speech and audio: Image enhancement Image recognition Medical imaging Image forensics Image coding Digital Image Processing: Internet audio, video, phones Image / video compression Text-to-voice & voice-to-text Movie indexing Multimedia: …….. CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Sampling For a given sampling interval T, which is defined as the time span between two sample points, the sampling rate is given by samples per second (Hz). For example, if a sampling period is T = 125 microseconds, the sampling rate is determined as fs =1/125 s or 8,000 samples per second (Hz). Sample and Hold CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Sampling - Theorem Freq. = 2 / 23 Freq. = 7 / 23 Freq. = 22/ 23 CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Sampling - Theorem The sampling theorem guarantees that an analog signal can be in theory perfectly recovered as long as the sampling rate is at least twice as large as the highest-frequency component of the analog signal to be sampled. The condition is: For example, to sample a speech signal containing frequencies up to 4 kHz, the minimum sampling rate is chosen to be at least 8 kHz, or 8,000 samples per second. CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Sampling - Theorem Sampling interval T= 0.01 s Sampling rate fs= 100 Hz Sinusoid freq. = 4 cycles / 0.1 = 40 Hz Sampling condition is satisfied, so reconstruction from digital to analog is possible. Do this by yourself! CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Sampling Process x(t): Input analog signal p(t): Pulse train CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Sampling Process In frequency domain: Xs(f): Sampled spectrum X(f): Original spectrum X(fnfs): Replica spectrum CEN352, Dr. Ghulam Muhammad King Saud University

Sampling Process Original spectrum Original spectrum plus its replicas Minimum requirement for Reconstruction Reconstruction not possible Original spectrum plus its replicas CEN352, Dr. Ghulam Muhammad King Saud University

Shannon Sampling Theorem For a uniformly sampled DSP system, an analog signal can be perfectly recovered as long as the sampling rate is at least twice as large as the highest-frequency component of the analog signal to be sampled. Half of the sampling frequency fs/2 is usually called the Nyquist frequency (Nyquist limit), or folding frequency. CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Example 1 Problem: Solution: Using Euler’s identity, Hence, the Fourier series coefficients are: CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Example 1 – contd. a. b. After the analog signal is sampled at the rate of 8,000 Hz, the sampled signal spectrum and its replicas centered at the frequencies nfs, each with the scaled amplitude being 2.5/T Replicas, no additional information. CEN352, Dr. Ghulam Muhammad King Saud University

Signal Reconstruction First, the digitally processed data y(n) are converted to the ideal impulse train ys(t), in which each impulse has its amplitude proportional to digital output y(n), and two consecutive impulses are separated by a sampling period of T; second, the analog reconstruction filter is applied to the ideally recovered sampled signal ys(t) to obtain the recovered analog signal. CEN352, Dr. Ghulam Muhammad King Saud University

Signal Reconstruction CEN352, Dr. Ghulam Muhammad King Saud University

Signal Reconstruction Aliasing Perfect reconstruction is not possible, even if we use ideal low pass filter. CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Example 2 Problem: Solution: Using the Euler’s identity: CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Example 2 – contd. a. b. The Shannon sampling theory condition is satisfied. CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Example 3 Problem: Solution: a. b. CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Quantization L: No. of quantization level m: Number of bits in ADC : Step size of quantizer i: Index corresponding to binary code xq: Quantization level xmax: Max value of analog signal xmin: Min value of analog signal Example: Unipolar CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Quantization – contd. Bipolar CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Example 4 Problem: Solution: c. a. b. Quantization error: d. 101 CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Periodicity In discrete-time case, a periodic sequence is a sequence for which where the period N is necessarily an integer. Example: Period of N = 8 CEN352, Dr. Ghulam Muhammad King Saud University

CEN352, Dr. Ghulam Muhammad King Saud University Periodicity Example: Not periodic with N = 8 But periodic with N = 16 However, is not periodic, because there is no such N. Determine whether the following signals are periodic or not. CEN352, Dr. Ghulam Muhammad King Saud University