DSP-Lec 00-Introduction

Chapter p Introduction Ha Hoang Kha, Ph.D.Click to edit Master subtitle style Ho Chi Minh City University of Technology @ Email: hhkha@hcmut.edu.vn Signal and Systems ™ A signal is defined as any physical quantity that varies with time, space or an space, any other independent variables ariables ‰ Speech, image, video and electrocardiogram signals are information-bearing signals g ™ Mathematically, we describe a signal as a function of one or more independent p variables ‰ Examples: x(t ) = 110sin(2π ⋅ 50t ) I ( x, y ) = x + xy + 10 y ™ A system is defined as a physical device that performs any operation g on a signal ‰ A filter is used to reduce noise and interference corrupting a desired information-bearing signal Ha H Kha Introduction Signal and Systems ™ Signal processing is to pass a signal through h h a system ™ A digital system can be implemented as a digital computer or digital hardware (logic circuits) Ha H Kha Introduction 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 m ltichannel signals ‰ Ex: 3-lead and 12-lead electrocardiograms (ECG) are often used in practice, which results in 33-channel channel and 12-channel 12 channel signals signals ™ A signal is called M-dimensional if its value is a function of M independent d d variable b ‰ 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) Ha H Kha 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(n) ( ) (t) x(t) Continuous t n Analog signal xQ(t) Discrete t Quantized signal Ha H Kha Discrete time signal 111 xQ(n) 110 101 100 011 n 010 001 000 Digital signal Digital signal  Introduction Basic elements of a DSP system ™ Most of the signals encountered in science and engineering are analog in nat nature re To perform the processing digitall digitally, there is a need for an interface between the analog signal and the digital processor Fig: Analog signal processing Fi Digital Fig: Di i l signal i l processing i Ha H Kha Introduction DSP applications-Communications ™ Telephony: transmission of information in digital form via telephone lines, modem technology, mobile phone ™ Encoding and decoding of the information sent over physical channels h nn l (t (to optimize ptimiz transmission, to detect or correct co ect errors e o s in transmission) t a s ss o ) Ha H Kha Introduction DSP applications-Radar Radar and sonar: ™ Target detection: position and velocity estimation ™ Tracking Ha H Kha Introduction DSP applications-Biomedical ™ Analysis of biomedical signals, diagnosis, patient monotoring, pre enti e health care, preventive care artificial organs organs ™ Examples: ™ Electrocardiogram l di (ECG) ( CG) signal i l provides id information about the condition of the patient’ss heart patient heart ™ Electroencephhalogram (EEG) signal pro ides information abo provides aboutt the activity of the brain Ha H Kha Introduction DSP applications-Speech ™ Noise reduction: reducing backgro nd noise in the sequence background seq ence produced by a sensing device (a microphone) p ) ™ Speech recognition: differentiating between various speech sounds ™ Synthesis of artificial speech : text to speech systems Ha H Kha 10 Introduction DSP applications-Image Processing ™ Content based image retrievalbro sing searching and retrie browsing, retrieving ing images from database ™ Image enhancement ™ Compression: reducing the g data to redundancyy in the image optimize transmission/storage Ha H Kha 11 Introduction DSP applications-Multimedia ™ Generation storage and transmission of sound, so nd still images images, motion pictures ™ Digital TV ™ Video conference Ha H Kha 12 Introduction The Journey “ Learning L i digital di i l signal i l processing i is i not something hi you accomplish; it’s a journey you take” R.G Lyons, Understanding Digital Signal Processing Ha H Kha 13 Introduction Advantages of digital over analog signal processing ™ A digital programmable system allows flexibility in reconfiguring the DSP operations simply by changing the program ™ A digital system provides much better control of accuracy requirements ™ Digital g signals g are easilyy stored ™ DSP methods allow for implementation of more sophisticated signal processingg algorithms p g ™ Limitation: Li it ti Practical P ti l limitations li it ti off DSP are the th quantization ti ti errors and the speed of A/D converters and digital signal processors -> not suitable for analog signals with large bandwidths Ha H Kha 14 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 Ha H Kha 15 Introduction References ™ Text T t books: b k [1]  S. J. Orfanidis, Introduction to Signal Processing, Prentice –Hall  Publisher 2010 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 [3] V. K. Ingle, J. Proakis, Digital Signal Processing Using Matlab,  Cengage Learning, 3 Edt, 2011.  Ha H Kha 16 Introduction Learning outcomes ™ Understand how to convert the analog to digital signal  ™ Have Have a thorough grasp of signal processing in linear time‐invariant  a thorough grasp of signal processing in linear time invariant systems ™ Understand the z‐transform and Fourier transforms in analyzing  the signal and systems the signal and systems ™ Be able to design and implement FIR and IIR filters Ha H Kha 17 Introduction Assessment ™ Mid‐term exam:  30% ™ Final exam:  70% ™ Bonus:  0.5 mark/solving a problem in the class Ha H Kha 18 Introduction