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Acquisition and Signal Processing

Code: ACSPI4001     Acronym: ACSPI4001

Keywords
Classification Keyword
OFICIAL Automation, Control & Manufacturing Syst.

Instance: 2018/2019 - 2S

Active? Yes
Web Page: https://sigarra.up.pt/feup/pt/conteudos_adm.list?pct_pag_id=249640&pct_parametros=pv_ocorrencia_id=425935
Responsible unit: Department of Electrical and Computer Engineering
Course/CS Responsible: Master's Degree in Physical Engineering

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
MI:EF 20 study plan from 2017/18 4 - 6 56 162

Teaching Staff - Responsibilities

Teacher Responsibility
Carlos João Rodrigues Costa Ramos

Teaching - Hours

Lectures: 2,00
Laboratory Practice: 2,00
Type Teacher Classes Hour
Lectures Totals 1 2,00
Carlos João Rodrigues Costa Ramos 2,00
Laboratory Practice Totals 1 2,00
António Manuel Elias de Morais Carrapatoso 2,00

Teaching language

Portuguese

Objectives

This course aims to equip students with the knowledge necessary for mastery of basic concepts, methods, techniques and tools for the identification, analysis and design of systems: - Acquisition of signals from the continuous domain to the digital domain, - Signal processing in the digital domain and - Translating the signals output to the continuous domain or other domains according to the application in question.

Learning outcomes and competences

After successful completion of the course the student is able to: Identifying, analyzing and projecting the following blocks: the sensor signal conditioning, analog-digital conversion, digital signal processing and analog-digital conversion by selecting the most appropriate technology for the application being treated. Understanding the mathematical representation of signals in the continuous domain, discrete and digital as well as their relationship. Understanding the mathematical representation of signals in the time domain and frequency as well as their relationship. Understand sampling and reconstruction of signals, including the implications and conditions that must be made. Understanding the meaning and use of Fourier transforms and Z. Analyze digital filters and projecting them through specified objectives. Apply the techniques of digital signal processing in control systems.

Working method

Presencial

Program

Signal conditioning. Analog-digital converters (ADC). Digital-analog converters (zero order hold DAC, sigma-delta DAC and PWM). Characterization and representation of discrete signals and systems. Correlation and convolution of signals. Discrete Fourier transform and characterization of signals in the frequency domain. Z Transform. Sampling and reconstruction of signals. Characterization of Invariant and Linear Systems (LI) in the frequency domain. FIR and IIR project filters and their discrete structures realizations. The Discrete Fourier Transform (DFT) and its calculation by Fast Fourier Transform (FFT). Application of the FFT fast convolution FIR, in studies of correlation and spectral estimation. Application of digital signal processing in control systems. Platforms for the acquisition, implementation and performance of systems based on digital signal processing.

Mandatory literature

Alan V. Oppenheim, Ronald W. Schafer, John R. Buck; Discrete-time signal processing. ISBN: 0-13-083443-2
Francisco José de Oliveira Restivo; Processamento Digital de Sinal - Tópicos, 1998
Francisco Restivo e Aníbal Ferreira; Compilação de problemas de PDS, 2005
H. Rosemary Taylor; Data acquisition for sensor systems. ISBN: 0-412-78560-9

Complementary Bibliography

Steven W. Smith; The Scientist and Engineer's Guide to Digital Signal Processing
Ramón Pallás-Areny, John G. Webster; Analog signal processing. ISBN: 0-471-12528-8
luis Chaparro; signals and systems using MATLAB. ISBN: 978 0 12 394812 0

Teaching methods and learning activities

The lectures illustrate the issues to be discussed, using a philosophy of active learning, with examples of application and design of typical case studies. In laboratory classes are developed skills for mastery of tools and platforms for the implementation of digital signal processing in the real world. Integrating projects are also conducted to familiarize students with the potential applications of the knowledge acquired. The performance and behavior of students in these classes is evaluated (LC).

Software

Maple
Matlab
Code Composer Studio (Texas Instruments)

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation Weight (%)
Exame 60,00
Trabalho laboratorial 40,00
Total: 100,00

Amount of time allocated to each course unit

Designation Time (hours)
Estudo autónomo 78,00
Frequência das aulas 56,00
Trabalho laboratorial 28,00
Total: 162,00

Eligibility for exams

Students will be admitted to the Final Exam (FE) if they attend practical classes and if they reach a minimum mark of EIGHT(8) out of TWENTY (20) in the laboratory component (LC).

Calculation formula of final grade

Final Mark will be based on the following formula: 0.6*FE + 0.4*LCx.
FE- Final Exam.
LCx - Laboratory Component with mark upper limited by the Final Exam.
LC- Laboratory Component.
The LCx mark cannot exceed the FE by more than 4 points: TLx = min(TL, EF+4)
To complete the course, students have to reach a minimum mark of 8 out of 20 in the Final Exam and in the laboratory component.
All of the components will be graded from 0 to 20 rounded to the unit.

Examinations or Special Assignments

None.

Special assessment (TE, DA, ...)

Working students, military personnel and students association leaders who did not attend to practical classes, will have to attend a practical exam.

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