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Lecturer(s)
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Holada Miroslav, Ing. Ph.D.
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Course content
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Lectures: 1) Architecture of DSP, programming of DSP, input-output devices. 2) Instruction set of DSP (Texas Instruments TMS), difference between DSP and GPP 3) Programming methods, linear programming, machine code, high-level programming language (C). 4) Connecting peripherals, A/D and D/A converters, memory and external hardware. 5) Digital signal and transmitted information, sampling and quantization, presentation of a signal, numerical stability. 6) Analysis of digital signals in the time domain. Digital filters FIR and IIR, convolution and their implementation in DSP. 7) Analysis of the digital signal in the frequency domain. FFT and its implementation, data preparation, presentation of results. 8) Signal filtering, noise reduction. 9) Data processing in real time. Use of interruption. 10) Examples of application with digital signal processors. Project Scrambler, DTMF. 11) Alternative processors for digital signal processing. 12) BeagleBoard-xM kit. 13) Overview of the latest available technologies from leading manufacturers of processors. 14) Summary. Practice: 1) Structure development boards with digital signal processor. 2) The Code Composer Studio (6th or higher), the possibility of programming and debugging programs. 3) Programming in a higher programming language C, operations used in DSP. 4) Communication with peripheral devices and the host computer. 5) Sampling, verification sampling theorem, data presentation. 6) Basic methods of analysis time. 7) Mean, short-term energy and the number of zero-crossings of the digital signal. 8) Design FIR and IIR filters in MATLAB and their implementation in DSP. 9) Implementation filter type DP, HP, PP and PZ. Testing on real data. 10) Amplitude modulation and project Scrambler. 11) Identification of a periodic signal in noise using the autocorrelation function. FFT. 12) Generation and decoding DTMF signal. 13) Alternative hardware for implementing DSP tasks - single board computer BeagleBoard-xM 14) Sample applications and projects of BeagleBoard.
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Learning activities and teaching methods
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Monological explanation (lecture, presentation,briefing)
- Class attendance
- 56 hours per semester
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Learning outcomes
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The subject provides an introduction to digital signal processor (DSP) technique. Students learn a typical DSP architecture, approches to DSP programming, algorithms for real-time signal processing, interfacing issues, etc. In excercises, students use DSP starter boards to implement tasks from time and frequency domain analysis, convolution, FFT, filtering, etc.
Theoretic piece of knowledge and practical skills from requered areas
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Prerequisites
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Condition of registration: Knowledge of digital signal processing, programming.
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Assessment methods and criteria
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Combined examination, Written exam
Examination is of the written form, understanding the problems solved at the seminars and understanding the lectured topics are required. Activity on the seminars and successful passing the tests are required for getting a credit. Examination is of the written form. Understanding of the lectured topics is required.
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Recommended literature
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Dvořák, V. - Drábek. V. Architektura procesorů. VUT Brno, 1999..
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Hlavička, J. Architektura počítačů. Skriptum ČVUT FEL, Praha 1996..
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McClellan J.H., Schafer R., Yoder M.A. DSP First - A Multimedia Approach. Prentice Hall, 1998..
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Smékal, Z., Vích, R. Zpracování signálů pomocí signálových procesorů. Radix. Praha, 1998..
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