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Bài giảng Xử lý tín hiệu số - Chapter 0: Introduction has contents: Signal and systems, classification of signal, basic elements of a DSP system, DSP applications - communications,... and other contents.
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 CuuDuongThanCong.com https://fb.com/tailieudientucntt 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 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt 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 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt 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 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt 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 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt 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 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt 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 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt DSP applications-Radar Radar and sonar: Target detection: position and velocity estimation Tracking Ha H Kha CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt 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 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt 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 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt 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 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt DSP applications-Multimedia Generation storage and transmission of sound, so nd still images images, motion pictures Digital TV Video conference Ha H Kha 12 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt 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 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt 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 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt 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 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt 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 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt 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 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt Assessment Mid‐term exam: 30% Final exam: 70% Bonus: 0.5 mark/solving a problem in the class Ha H Kha 18 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt ... Continuous t n Analog signal xQ(t) Discrete t Quantized signal Ha H Kha Discrete time signal 111 xQ(n) 1 10 101 100 01 1 n 01 0 00 1 00 0 Digital signal Digital signal CuuDuongThanCong.com Introduction... 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... Ha H Kha 17 CuuDuongThanCong.com Introduction https://fb.com/tailieudientucntt Assessment Mid‐term exam: 30% Final exam: 70% Bonus: 0. 5 mark/solving a problem in the class Ha H Kha 18