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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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Topics of lectures: - Current architecture of processors suitable for digital signal processing, their programming, I / O devices. - Digital signal and transmitted information, sampling and sampling theorem, quantization. - Methods of programming, machine code, higher programming language (C). Options for debugging and testing written code. Real-time data processing. - Connection of A / D, D / A converters, memory and other peripherals via I2C, SPI, UART and other interfaces. - Analysis and synthesis of signals in the time domain. Generation of harmonic signals. - Digital FIR and IIR filters, their design and structure in Matlab and implementation in own processor. - Analysis of digital signal in the frequency domain. FFT and its implementation, data preparation, presentation of results. - Possibilities of LTI systems and nonlinear processes - modulation. - Basic implementable audio effects. - Machine recognition algorithms, implementation of a recognizer with a trained neural network. Contents of laboratory exercises: - Development environments of leading manufacturers of processors and controllers suitable for signal processing. - Programming in a higher level programming language (C / C ++) and options for debugging written code (SWD / JTAG). - Communication with peripheral devices and the superior computer. - Sampling, verification of sampling theorem, anti-alliasing filters, data presentation. - Basic methods of time analysis. Mean value, short-term energy and number of zero crossings of a digital signal. - Application of a convolution product for a one-dimensional signal. - Design of FIR and IIR filters in MATLAB and their implementation. Implementation of DP, HP, PP and PZ. SoS structure, numerical stability. - Identification of periodic signal in noise using autocorrelation function. - Possibilities of FFT implementation. - DTMF signal generation and decoding. - Project "SCRAMBLER", AM. - Basic audio effects. Audio codecs. - Implementation of a trained neural network and verification of functionality. - Realization of own independent semester task.
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Learning activities and teaching methods
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Monological explanation (lecture, presentation,briefing), Laboratory work, Lecture, Practicum
- Preparation for credit
- 34 hours per semester
- Preparation for exam
- 20 hours per semester
- Class attendance
- 56 hours per semester
- Home preparation for classes
- 40 hours per semester
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Learning outcomes
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The aim of the course is to connect the knowledge of digital signal processing, knowledge of programming and processor structure in examples on real hardware. The course introduces the practical application and deployment of digital signal processing algorithms on real processors. Implementations of basic digital signal processing methods are presented with concrete examples. The method of programming and algorithmization of real-time processing tasks, available input and output peripherals and their capabilities are discussed. Methods of time and frequency analysis and synthesis, algorithms for calculating convolution, correlation, FFT and the possibilities of designing digital filters are presented with practical examples. Parameter design and verification is performed in Matlab environment. The algorithms are implemented on processors of "Texas Instruments" and "STMicroelectronics" companies. At the end of the course the possibilities of implementing machine recognition and neural networks are mentioned.
Theoretic piece of knowledge and practical skills from requered areas
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Prerequisites
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Prerequisite for registration: knowledge at the level of basic courses in mathematics, digital signal processing, programming in C language and work in MATLAB.
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Assessment methods and criteria
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Combined examination
The condition of the credit is active participation in exercises and successful solution of assigned tasks. The exam is written and oral.
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Recommended literature
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CHASSAING, Rulph a Donald REAY. Digital signal processing: and applications with the TMS320C6713 and TMS320C6416 DSK. 2nd ed.. John Wiley & Sons, 2008. ISBN 978-0-470-13866-3.
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LANGBRIDGE, By James A. Professional embedded arm development. Indianapolis,. 2013. ISBN 9781118788943.
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SMÉKAL, Zdeněk a Petr SYSEL. Signálové procesory. 1. vyd.. Praha, 2006. ISBN 80-86645-08-8.
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