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8202014 1 Click to edit Master subtitle style Introduction Chapter 0 Ha Hoang Kha, Ph.D.Click to edit Master subtitle style Ho Chi Minh City University of Technology Email: hhkhahcmut.edu.vn Introduction Chapter 0 CuuDuongThanCong.com https:fb.comtailieudientucntt8202014 2 Digital Signal Processing A signal is defined as any physical quantity that varies with time, space, or any other independent variables. 1. Signal and Systems 3 Speech, image, video and electrocardiogram signals are informationbearing signals. Mathematically, we describe a signal as a function of one or more independent variables. Examples: x t t ( ) 110sin(2 50 ) I x y x xy y ( , ) 3 2 10 2 A system is defined as a physical device that performs any operation on a signal. A filter is used to reduce noise and interference corrupting a desired informationbearing signal. Introduction Digital Signal Processing Signal processing is to pass a signal through a system. 1. Signal and Systems 4 A digital system can be implemented as a digital computer or digital hardware (logic circuits). Introduction CuuDuongThanCong.com https:fb.comtailieudientucntt8202014 3 Digital Signal Processing Multichannels and Multidimensional signals 2. Classification of Signal 5 Signals which are generated by multiple sources or multiple sensors can be represented in a vector form. Such a vector of signals is referred to as a multichannel signals Ex: 3lead and 12lead electrocardiograms (ECG) are often used in practice, which results in 3channel and 12channel signals. A signal is called Mdimensional if its value is a function of M independent variable Picture: the intensity or brightness I(x,y) at each point is a function of 2 independent variables Color TV picture is 3dimensional signals I(x,y,t) Introduction Digital Signal Processing Continoustime versus discretetime signal 2. Classification of Signal 6 Signals can be classified into four different categories depending on the characteristics of the time variable and the values they take. Introduction Time Amplitue Continuous Discrete Continuous Analog signal Discrete time signal Discrete Quantized signal Digital signal t x(t) n x(n) n x Q(n) xQ(t) t 000 001 010 100 101 110 111 011 CuuDuongThanCong.com https:fb.comtailieudientucntt8202014 4 Prof. Trac Tran. Click to edit Master subtitle style John Hopskin University, USA Introduction Chapter 0 Digital Signal Processing 2. Classification of Signal 8 Introduction ContinuousAmplitude DiscreteAmplitude Continuous Time (Space) Local telephone, cassettetape recording playback, phonograph, photograph telegraph Discrete Time (Space) Switched capacitor filter, speech storage chip, halftone photography CD, DVD, cellular phones, digital camera camcorder, digital television, inkjet printer t x(t) t x(t) n xn n xn CuuDuongThanCong.com https:fb.comtailieudientucntt8202014 5 2. Classification of Signal Digital Signal Processing 3. Basic elements of a DSP system 10 Introduction • AnalogtoDigital conversion (ADC) – Process of converting a continuoustime signal into its discretetime representation – Sampling = Digitizing – Reverse process is DigitaltoAnalog conversion (DAC) • Issues to consider in ADC – Can we get back our original analog signal? – If yes, what conditions should be satisfied so that the original signal is not altered? – If no, how can we minimize the error difference? analog ADC DSP ADC signal digital signal digital signal analog signal CuuDuongThanCong.com https:fb.comtailieudientucntt8202014 6 Digital Signals Everywhere • Fax machines: transmission of binary images • Digital cameras: still images • iPod iPhone MP3 • Digital camcorders: video sequences with audio • Digital television broadcasting • Compact disk (CD), Digital video disk (DVD) • Personal video recorder (PVR, TiVo) • Images on the World Wide Web • Video streaming conferencing • Video on cell phones, PDAs • Highdefinition televisions (HDTV) • Medical imaging: Xray, MRI, ultrasound, telemedicine • Military imaging: multispectral, satellite, infrared, microwave Digital Bit Rates • A picture is worth a thousand words? • Size of a typical color image – For display • 640 x 480 x 24 bits = 7372800 bits = 92160 bytes – For current mainstream digital cameras (5 Megapixel) • 2560 x 1920 x 24 bits = 117964800 bits = 14745600 bytes – For an average word • 45 charactersword, 7 bitscharacter: 32 bits ~= 4 bytes • Bit rate: bits per second for transmission – Raw digital video (DVD format) • 720 x 480 x 24 x 24 frames: ~200 Mbps – CD Music • 44100 samplessecond x 16 bitssample x 2 channels ~ 1.4 Mbps CuuDuongThanCong.com https:fb.comtailieudientucntt8202014 7 Reasons for Compression • Digital bit rates – Terrestrial TV broadcasting channel: ~20 Mbps – DVD: 10...20 Mbps – EthernetFast Ethernet: not suitable for analog signals with large bandwidths. Introduction Digital Signal Processing Course overview 36 Introduction Introduction to Digital Signal Processing (3 periods) Midterm Exam Fourier transform FFT Algorithm (9 periods) Sampling and reconstruction, quantization (6 periods) Analysis of linear time invariant systems (LTI)(3 periods) Finite Impulse Response (FIR) of LTI systems (3 periods) Ztransform and its applications to the analysis of linear systems (6 periods) Digital filter realization(3 periods) FIR and IIR filter designs (9 periods) Final Exam CuuDuongThanCong.com https:fb.comtailieudientucntt8202014 19 Digital Signal Processing Text books: 1 S. J. Orfanidis, Introduction to Signal Processing, Prentice –Hall Publisher 2010. 2 J. Proakis, D. Manolakis, Introduction to Digital Signal Processing, Macmillan Publishing Company, 1989. References 37 Introduction Reference books: 3 V. K. Ingle, J. Proakis, Digital Signal Processing Using Matlab, Cengage Learning, 3 Edt, 2011. Digital Signal Processing Learning outcomes 38 Introduction Understand how to convert the analog to digital signal Be able to design and implement FIR and IIR filters. Have a thorough grasp of signal processing in linear timeinvariant systems. Understand the ztransform and Fourier transforms in analyzing the signal and systems. CuuDuongThanCong.com https:fb.comtailieudientucntt8202014 20 Digital Signal Processing Assessment 39 Introduction Midterm exam: 40% Final exam: 60% CuuDuongThanCong.com https:fb.comtailieudientucntt
8/20/2014 Chapter Introduction Click to edit Master subtitle style Chapter Introduction Ha Hoang Kha, Ph.D.Click to edit Master subtitle style Ho Chi Minh City University of Technology Email: hhkha@hcmut.edu.vn CuuDuongThanCong.com https://fb.com/tailieudientucntt 8/20/2014 Signal and Systems A signal is defined as any physical quantity that varies with time, space, or any other independent variables Speech, image, video and electrocardiogram signals are information-bearing signals Mathematically, we describe a signal as a function of one or more independent variables Examples: x(t ) 110sin(2 50t ) I ( x, y) 3x xy 10 y A system is defined as a physical device that performs any operation on a signal A filter is used to reduce noise and interference corrupting a desired information-bearing signal Digital Signal Processing Introduction Signal and Systems Signal processing is to pass a signal through a system A digital system can be implemented as a digital computer or digital hardware (logic circuits) Digital Signal Processing CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt 8/20/2014 Classification of Signal Multichannels and Multidimensional signals Signals which are generated by multiple sources or multiple sensors can be represented in a vector form Such a vector of signals is referred to as a multichannel signals Ex: 3-lead and 12-lead electrocardiograms (ECG) are often used in practice, which results in 3-channel and 12-channel signals A signal is called M-dimensional if its value is a function of M independent variable Picture: the intensity or brightness I(x,y) at each point is a function of independent variables Color TV picture is 3-dimensional signals I(x,y,t) Digital Signal Processing Introduction Classification of Signal Continous-time versus discrete-time signal Signals can be classified into four different categories depending on the characteristics of the time variable and the values they take Time Continuous Discrete Amplitue x(t) x(n) Continuous t n Analog signal xQ(t) Discrete t Quantized signal Digital Signal Processing CuuDuongThanCong.com Discrete time signal 111 xQ(n) 110 101 100 011 n 010 001 000 Digital signal Introduction https://fb.com/tailieudientucntt 8/20/2014 Chapter Introduction Prof Trac Tran Click to edit Master subtitle style John Hopskin University, USA Classification of Signal Continuous-Amplitude x(t) Continuous -Time (Space) x(t) t Digital Signal Processing CuuDuongThanCong.com t Local telephone, cassette-tape recording & playback, phonograph, photograph telegraph x[n] x[n] Discrete -Time (Space) Discrete-Amplitude n n Switched capacitor filter, speech storage chip, half-tone photography CD, DVD, cellular phones, digital camera & camcorder, digital television, inkjet printer Introduction https://fb.com/tailieudientucntt 8/20/2014 Classification of Signal Basic elements of a DSP system analog signal ADC digital signal DSP digital signal ADC analog signal • Analog-to-Digital conversion (ADC) – Process of converting a continuous-time signal into its discrete-time representation – Sampling = Digitizing – Reverse process is Digital-to-Analog conversion (DAC) • Issues to consider in ADC – Can we get back our original analog signal? – If yes, what conditions should be satisfied so that the original signal is not altered? – If no, how can we minimize the error difference? Digital Signal Processing CuuDuongThanCong.com 10 Introduction https://fb.com/tailieudientucntt 8/20/2014 Digital Signals Everywhere! • • • • • • • • • • • • • Fax machines: transmission of binary images Digital cameras: still images iPod / iPhone & MP3 Digital camcorders: video sequences with audio Digital television broadcasting Compact disk (CD), Digital video disk (DVD) Personal video recorder (PVR, TiVo) Images on the World Wide Web Video streaming & conferencing Video on cell phones, PDAs High-definition televisions (HDTV) Medical imaging: X-ray, MRI, ultrasound, telemedicine Military imaging: multi-spectral, satellite, infrared, microwave Digital Bit Rates • A picture is worth a thousand words? • Size of a typical color image – For display • 640 x 480 x 24 bits = 7372800 bits = 92160 bytes – For current mainstream digital cameras (5 Mega-pixel) • 2560 x 1920 x 24 bits = 117964800 bits = 14745600 bytes – For an average word • 4-5 characters/word, bits/character: 32 bits ~= bytes • Bit rate: bits per second for transmission – Raw digital video (DVD format) • 720 x 480 x 24 x 24 frames: ~200 Mbps – CD Music • 44100 samples/second x 16 bits/sample x channels ~ 1.4 Mbps CuuDuongThanCong.com https://fb.com/tailieudientucntt 8/20/2014 Reasons for Compression • Digital bit rates – – – – – – – Terrestrial TV broadcasting channel: ~20 Mbps DVD: 10 20 Mbps Ethernet/Fast Ethernet: not suitable for analog signals with large bandwidths Digital Signal Processing 35 Introduction Course overview Introduction to Digital Signal Processing (3 periods) Sampling and reconstruction, quantization (6 periods) Analysis of linear time invariant systems (LTI)(3 periods) Finite Impulse Response (FIR) of LTI systems (3 periods) Z-transform and its applications to the analysis of linear systems (6 periods) Mid-term Exam Fourier transform & FFT Algorithm (9 periods) Digital filter realization(3 periods) FIR and IIR filter designs (9 periods) Final Exam Digital Signal Processing CuuDuongThanCong.com 36 Introduction https://fb.com/tailieudientucntt 18 8/20/2014 References Text books: [1] S J Orfanidis, Introduction to Signal Processing, Prentice –Hall Publisher 2010 [2] J Proakis, D Manolakis, Introduction to Digital Signal Processing, Macmillan Publishing Company, 1989 Reference books: [3] V K Ingle, J Proakis, Digital Signal Processing Using Matlab, Cengage Learning, Edt, 2011 Digital Signal Processing 37 Introduction Learning outcomes Understand how to convert the analog to digital signal Have a thorough grasp of signal processing in linear time-invariant systems Understand the z-transform and Fourier transforms in analyzing the signal and systems Be able to design and implement FIR and IIR filters Digital Signal Processing CuuDuongThanCong.com 38 Introduction https://fb.com/tailieudientucntt 19 8/20/2014 Assessment Mid-term exam: 40% Final exam: 60% Digital Signal Processing CuuDuongThanCong.com 39 Introduction https://fb.com/tailieudientucntt 20 ... 3.3kHz f sampling 6.6kHz 300Hz-3.5kHz f (Hz) 10k 20k Speech Signals ph - o - n - e - CuuDuongThanCong.com t - i - c - ia - n Main useful frequency range of human voice: 300 Hz – 3.4 kHz https://fb.com/tailieudientucntt... signal • Analog-to-Digital conversion (ADC) – Process of converting a continuous-time signal into its discrete-time representation – Sampling = Digitizing – Reverse process is Digital-to-Analog conversion... multichannel signals Ex: 3-lead and 12-lead electrocardiograms (ECG) are often used in practice, which results in 3-channel and 12-channel signals A signal is called M-dimensional if its value