. "Advanced telecommunication system applications and services"@en . . "7.5" . "GNSS, Navigation" . . "Hybrid"@en . "FALSE" . . "Digital signals processing in avionics equipment"@en . . "4.5" . "The subject's \"Digital Processing of Signals avionic devices” purpose is to introduce students to digital signal processing key trends and theoretical foundations. The subject discusses application of digital processing algorithms to aircraft navigation and radiolocation systems.\n\nOutcome:\nThe student knows digital signal processing, the trends and digital processing advantages. - Final examination question.\r\nThe student knows mathematical signal processing techniques, is able to use them to solve practical problems. - Independent work, practical work and final examination question.\r\nThe student knows digital filter synthesis techniques, is able to display filter circuit and the impulse response of the filter transmission functions. - Practical work and final examination question.\r\nThe student knows digital aircraft radio navigation system advantages, is able to analyze a system of functional circuitry. - Practical work and final examination question.\r\nThe student knows digital signal processing tasks and methods of radiolocation systems, is able to analyze appropriate system algorithms and signal processing techniques advantages. - Practical work and final examination question." . . "Presential"@en . "TRUE" . . "Space communication"@en . . "7.5" . "The course will cover: \n1. An overview of satellite and spacecraft communication systems;\n2. The conversions of signals and data into forms suitable for transmission over lines, optical fibres, waveguides\nand radio links;\n3. An introduction to information theory and capacity;\n4. Frequency translation, analogue and digital modulation, theory and systems;\n5. Noise, noise sources, noise figure, factor and temperature, system values and bit error rate;\n6. Antenna, arrays, polar diagrams, and gain; \n7. Link budgets. \n\nOutcome:\nThe aim of the course is to extend and deepen the student’s knowledge of digital and analogue communication\nsystems with an emphasis on space communications. On completion of the course the student shall have the skills\nand knowledge to be able to:\n1. Describe an overview of the forms of communication systems used for scientific satellites and spacecraft,\ncommunication satellites, broadcast satellites and for the Telemetry, Tracking and Control (TT&C) of\nspacecraft;\n2. Identify the technologies and requirements of the various parts of each of the above systems;\n3. Perform an analysis of a communication system or part of a communication system to determine items of the\r\nperformance such as the signal to noise ratio, the bit error rate, the capacity, the link utilization and the link\r\nbudget;\n4. Describe and make calculations and measurements on a number of techniques used to translate signals in\r\nthe frequency domain, to perform modulation and de-modulation and to form a number of channels through a\r\ncommunication system;\n5. Describe the principles of multiple access to communication satellites and to capacity assignment; \n6. Describe a number of methods used for forward and for backward error correction;\nCooperate with colleagues in undertaking practical projects and measurements and writing technical reports\nin English." . . "Presential"@en . "TRUE" . . "Signals and signal processing"@en . . "9" . "Course aim\r\nIncreasing of knowledge and skills in theoretical analysis of signals and their processing methods in newest technology. Be able to explain the proposed solution, self-employed or diverse.\r\n\r\nDescription\r\nThe course of Signals and Processing provides knowledge on the basic items of signal theory: the analysis techniques of signals changing in electronic circuits, dynamic signals mapping, geometrical methods of signal theory, orthogonal signals theory, methods of calculating the amount of information. The mathematical models of fixed range signals and their associated sampling theorem, analytical signal, Gilbert's transformation are analyzed. During the study of discrete signals and their processing the students learn to make mathematical models of discrete signals and calculate the signal characteristics. The skills to analyze creation, processing and utilization of digital signals are acquired. Analog-digital and digital-analog converters, the fast Fourier transform and its applications, digital filtering algorithms in time and frequency domain, the digital device speed are analyzed.\n\nOutcome: Not Provided" . . "Hybrid"@en . "FALSE" . . "Radioengineering and antennas"@en . . "5" . "Learning outcomes of the course unit:\nThe graduate of the course has an idea of electromagnetic (EM) fields excited by a harmonic quantity. Energy transfer through EM fields and the events that occur during this transfer.\n\nKnowledge and understanding\nAfter completing the course the student:\n- knows the transmission of energy through EM fields and the events that occur during this transmission,\n- knows the impact of individual obstacles on the propagation of the EM field,\n- knows the basic / elementary sources of EM fields.\n\nAcquired skills and competencies\n- ability to analyze and synthesize the radio-electronic chain,\n- ability to adapt the radiator to the transmission line,\n- ability to measure high frequency parameters of circuits,\n- ability to apply existing solutions to new problems associated with the transfer of information between space objects,\n- ability to design antennas,\n- the ability to design a solution, defend a solution, present a solution and work in a team to implement it. Course Contents:\nMaxwell equations (differential and integral form), boundary conditions, power and energy EM field. Wave equation and its solution for resource-free, loss-free environment, for loss-making environment in different co-ordination systems. Wave propagation and polarization, wave transition to the second environment, wave reflection, vertical impact, oblique impact. Elementary sources EM field, elementary dipole, elementary loop. Dipole with finite length, half wave dipole. Pocklington integral equation. Indoor and outdoor antenna tasks. Antenna systems. Radiocommunication equation. Methods and equipment for measuring electromagnetic parameters and fields." . . "Presential"@en . "FALSE" . . "Space communication"@en . . "5" . "Learning outcomes of the course unit:\nStudents will acquire basic knowledge concerning satellite and deep space communication challenges and approaches how to address them from information theory and communication theory point of view. Particularly they will know which channel models and signals are applicable in space communication and why transmission coding is inevitable for deep space communications and advantageous for satellite communication systems. They will know the concept of optimal receiver for linear and nonlinear modulations used in space communication, transmission codes starting from first used in space and finishing with up to date ones, how they are encoded and decoded using hard and soft methods starting from syndrome decoding and finishing with turbo and belief propagation decoding. They will be able to calculate link budget for space communication systems, know basic modulations and multi access method used in satellite communications systems. They will also become aware about application of communication and communication-like signals in telecommunication, navigation and sensing satellites Course Contents:\n1. Satellite, deep space and terrestrial communication systems and bandwidths for wireless communication;\n2. Channel models and signals applicable in space communication and their interaction with systems;\n3. Optimal receiver;\n4. Space communication from Information theory perspective;\n5. Channel capacity and why transmission codes are inevitable in space communication in AWGN channel;\n6. Convolutional codes-first transmission codes in applied in space;\n7. From first block codes applied in space- Golay codes to Reed Solomon codes;\n8. Up to date space codes;\n9. Link budget;\n10. Satellite systems;\n11. Multiple access in telecommunications satellites;\n12. Bandwidths, signals and transmission codes for satellite communication, navigation and sensing.." . . "Presential"@en . "FALSE" . . "Aerospace signals, systems and controls"@en . . "8" . "no data" . . "Presential"@en . "TRUE" . . "Signal theory"@en . . "6" . "Learning outcomes\n\nThe course approaches the study of continuous and discrete signals, in case obtained for sampling, and of the systems used for their processing. Representations in the time domain and in the frequency domain will be examined, putting in evidence both theoretical and fulfilling and simulation aspects. The objective is therefore to make the students familiar with the techniques for representing signals and to synthesize analogue and discrete filters for their processing." . . "Presential"@en . "FALSE" . . "Digital signal processing"@en . . "6" . "Learning outcomes\nAfter successful completion of the course, student ...\n1. is able to utilise A/D converter\n2. knows how to sample a continuous signal and describes possible distortions and noise\n3. calculates convolution of two discrete signals\n4. explains the principles of DFT and carries out relevant calculations\n5. determines FIR filter parameters h(k)\n6. designs suitable FIR filter for specific task\n7. understands the concept of IIR filter\nBrief description of content\nThe objective of the course is to give an introductory overview of the main topics of Digital Signal Processing. Lectures cover mainly sampling, transforms and digital filters. In laboratory experiments students have the opportunity to observe, explore and manipulate characteristics and behaviors of actual devices, systems, and processes." . . "Presential"@en . "TRUE" . . "Advanced signal processing 1 (8 crédits ects)"@en . . "8" . "SP4004E - Estimation/Detection\nSP5004E - Kalman Filtering\nAU409E - State Space Modeling, Analysis and Control\nSP4006E - Digital communications" . . "Presential"@en . "TRUE" . . "Advanced signal processing 2 (6 crédits ects)"@en . . "6" . "Digital Receivers\nArray signal processing\n Parametric modeling\nSpread Spectrum Techniques\nConcepts Avancés du GNSS : GPS L1 C/A receiver signal processing" . . "Presential"@en . "TRUE" . . "Data analysis and signal processing"@en . . "3" . "- Signal processing - this lecture presents deterministic and random signal processing methods.\n- Data analysis \n- Artifical Intelligence" . . "Presential"@en . "TRUE" . . "Foundations of signals and systems"@en . . "6" . "Objectives and Contextualisation\nIntroduce the student to the analysis and characterization of signals and systems, with emphasis on linear systems.\nLearn the Laplace transform and its properties.\nLearn how to apply the Laplace transform to circuit analysis.\nLearn and apply the concept of transfer function of an LTI system.\nLearn how to obtain the Bode diagram of a system.\nLearn the Fourier transform and its properties.\nLearn how to apply the Fourier transform to periodic signals (Fourier series) and the limitation in time (windowing) and frequency (Gibbs phenomenon).\nLearn and apply the concepts of energy and power of a signal.\nLearn and know how to apply the concepts of correlation and spectrum of signals\n\nCompetences\nElectronic Engineering for Telecommunication\nCommunication\nDevelop personal attitude.\nDevelop personal work habits.\nDevelop thinking habits.\nLearn new methods and technologies, building on basic technological knowledge, to be able to adapt to new situations.\nTelecommunication Systems Engineering\nCommunication\nDevelop personal attitude.\nDevelop personal work habits.\nDevelop thinking habits.\nLearn new methods and technologies, building on basic technological knowledge, to be able to adapt to new situations.\nLearning Outcomes\nAnalyse and design analogue signal processing diagrams.\nApply the basic concepts of linear systems and the related functions and transforms, to resolve engineering problems.\nAutonomously learn new and suitable knowledge and techniques for devising, developing or exploiting telecommunication systems, especially with regard to basic signal processing subsystems.\nCommunicate efficiently, orally and in writing, knowledge, results and skills, both professionally and to non-expert audiences.\nDescribe the fundamental parameters of a communications system, in the functional aspect.\nDevelop curiosity and creativity.\nDevelop independent learning strategies.\nDevelop the capacity for analysis and synthesis.\nManage available time and resources.\nManage available time and resources. Work in an organised manner.\nUse computer tools to research bibliographic resources or information on telecommunications and electronics.\nWork autonomously.\n\nContent\nIntroduction to the subject. Signals and systems.\nSignals. Independent variable transforms and basic signals.\nSystem properties: linearity, invariance, causality and stability.\nLinear and time invariant systems (LTI). Convolution equation.\nThe Laplace transform.\nLaplace transform. Definition. Properties.\nSolution of differential equations using the Laplace transform.\nObtaining the inverse Laplace transform.\nApplications of the Laplace transform.\nAnalysis of circuits with capacitors and inductors.\nTransfer function of a system. Definition and obtention of the impulse response.\nPole and zero diagrams and system stability.\nPermanent response of a system. Bode diagrams.\nThe Fourier transform.\nDefinition of the Fourier transform.\nTransform of basic signals.\nProperties of the Fourier transform.\nLimitation in frequency (Gibbs phenomenon) and limitation in time (windowing).\nFourier transform of periodic signals. The Fourier series.\nCorrelation and spectrum of deterministic signals.\nEnergy and power\nCorrelation and energy spectrum.\nCorrelation and power spectrum" . . "Presential"@en . "TRUE" . . "Discrete-time signals and systems"@en . . "6" . "Objectives and Contextualisation\nThe processing of sequences of numbers, also known as discrete signals, is a task present in virtually all information transmission, processing and storage systems, even when the source signals can be analog. The aim of the course is to provide the student with the fundamental knowledge to describe the discrete signals and the systems that deal with them, both in the temporal domain and in the frequency or transformed domains.\n\nThe specific goals are:\n\nTo understand the representation of discrete signals over time, as well as their properties.\nTo analyze the systems for the discrete signals processing over time and propose alternative ways of describing them.\nTo represent signals and systems in transformed domains: in the frequency domain and in the Z domain.\nTo design basic digital filters.\nTo relate discrete signals with the periodic sampling of analog signals and with their reconstruction.\nTo apply the Matlab programming environment to solve digital signal processing problems.\nTo characterize random discrete signals.\n\nCompetences\nElectronic Engineering for Telecommunication\nCommunication\nDevelop personal attitude.\nDevelop personal work habits.\nDevelop thinking habits.\nDraft, develop and sign projects in the field of telecommunications engineering designed to conceive, develop or exploit electronic systems\nLearn new methods and technologies, building on basic technological knowledge, to be able to adapt to new situations.\nResolve problems with initiative and creativity. Make decisions. Communicate and transmit knowledge, skills and abilities, in awareness of the ethical and professional responsibilities involved in a telecommunications engineer's work.\nWork in a multidisciplinary group and in a multilingual environment, and communicate, both in writing and orally, knowledge, procedures, results and ideas related with telecommunications and electronics\nWork in a team.\nTelecommunication Systems Engineering\nCommunication\nDevelop personal attitude.\nDevelop personal work habits.\nDevelop thinking habits.\nDraft, develop and sign projects in the field of telecommunications engineering that, depending on the speciality, are aimed at the conception, development or exploitation of telecommunication and electronic networks, services and applications.\nLearn new methods and technologies, building on basic technological knowledge, to be able to adapt to new situations.\nResolve problems with initiative and creativity. Make decisions. Communicate and transmit knowledge, skills and abilities, in awareness of the ethical and professional responsibilities involved in a telecommunications engineer's work.\nWork in a multidisciplinary group and in a multilingual environment, and communicate, both in writing and orally, knowledge, procedures, results and ideas related with telecommunications and electronics.\nWork in a team.\nLearning Outcomes\nAnalyse and design digital signal processing diagrams.\nCommunicate efficiently, orally and in writing, knowledge, results and skills, both professionally and to non-expert audiences.\nDevelop and seek basic signal processing applications other than for communications.\nDevelop curiosity and creativity.\nDevelop independent learning strategies.\nDevelop systemic thinking.\nDevelop the capacity for analysis and synthesis.\nDevise and seek basic applications for signal processing other than communications.\nEfficiently use ICT for the communication and transmission of ideas and results.\nIllustrate signal and communication processing algorithms using a basic mathematical formalism.\nIllustrate the algorithms of signal processing and communications using a basic mathematical formalism.\nMake basic use of computer applications in digital processing.\nMake one's own decisions.\nTransfer concepts of discreet mathematics to telecommunications, in the field of the processing of numerical series by means of digital filters.\nTransfer concepts of discrete mathematics to telecommunications, in the area of numerical series processing using digital filters\nUse computer applications for basic digital processing.\nWork autonomously.\nWork cooperatively.\n\nContent\n1. Signals and discrete systems\n\nSignals: properties, transformations and basic signals\nSystems: properties, basic systems\nConvolution\nDescription of systems using finite difference equations\n2. Frequency representation\n\nFourier transform (FT): definition, properties, convolution theorem\nDiscrete Fourier Transform (DFT): definition, properties, circular convolution\nCorrelation and spectrum\nDecimation and interpolation\n3. Sampling and reconstruction\n\nPeriodic sampling\nSampling representation in the frequency domain\nReconstruction of limited band signals: Nyquist Theorem\nModification of the sampling frequency\n4. Representation of signals and systems in the Z domain\n\nThe Z-transform: definition and properties\nThe inverse Z-transform\nFrequency response and transfer function\n5. System analysis\n\nInverse, minimum-phase and all-pass systems\nLinear phase systems\nIntroduction to the design of IR and IIR filters" . . "Presential"@en . "TRUE" . . "Digital signal processing"@en . . "12" . "Objectives and Contextualisation\nOnce completed the subject, the student will be able to:\n\nUse vector and matrix algebra normally.\nOperate with numerical series and stochastic processes.\nRigorously use different probabilistic tools.\nEstimate the parameters of a model from the signal samples at its output.\nEstimate the power spectral density of a random process.\nDesign optimal filters in the MMSE sense and implement them in an efficient manner using iterative/adaptive algorithms.\nApply signal processing techniques to situations in real life.\n\nCompetences\nApply deterministic and stochastic signal processing techniques to the design of communication subsystems and data analysis.\nDevelop personal attitude.\nDevelop personal work habits.\nDevelop thinking habits.\nLearn new methods and technologies, building on basic technological knowledge, to be able to adapt to new situations.\nPerform measurements, calculations, estimations, valuations, analyses, studies, reports, task-scheduling and other similar work in the field of telecommunication systems.\nLearning Outcomes\nAdapt the knowledge and techniques of the digital signal treatment in accordance with the characteristics of communication systems and services as well as fixed or mobile work scenario.\nAdapt to unforeseen situations.\nAnalyse and specify the fundamental parameters of communication subsystems from the point of view of the transmission, reception and digital treatment of signals.\nAnalyse the advantages and disadvantages of different technological alternatives or the implementation of communication systems from the point of view of digital signal treatment.\nApply adaptive statistical filtering and control theory to the design of dynamic algorithms for the coding, processing and transmission of multimedia information. Apply multichannel signal processing to the design of fixed and mobile antenna grouping based communication systems.\nApply detection and estimation theory to the design of communication receivers.\nApply statistical signal processing to estimate synchronisation parameters in digital communication and radio-navigation receivers.\nAutonomously learn new knowledge related with digital signal processing in order to conceive and develop communication systems.\nBe able to analyse, encode, process and transmit multimedia information employing analogue and digital signal processing techniques.\nDescribe the operational principles of radio-navigation, its architecture and the techniques for dealing with its sources of error.\nDevelop critical thinking and reasoning.\nDevelop curiosity and creativity.\nDevelop independent learning strategies.\nDevelop mathematical models to simulate the behaviour of communication subsystems and to evaluate and predict features.\nDevelop scientific thinking.\nDevelop the capacity for analysis and synthesis.\nGenerate innovative and competitive proposals in professional activity.\nManage available time and resources.\nManage information by critically incorporating the innovations of one's professional field, and analysing future trends.\nPropose innovative solutions for problems related with the transmission, reception and the digital treatment of signals.\nWork in complex or uncertain surroundings and with limited resources." . . "Presential"@en . "TRUE" . . "Microwave engineering"@en . . "6" . "Objectives and Contextualisation\nIn wireless communication systems the channel is an asset shared by different users and / or by different communication services. In this sense, communications systems use the electromagnetic spectrum in high frequency.\n\nThe subject of Microwave Engineering is focused on the design of specific components for the RF and Microwave communication equipment. Objectively, it deals with providing the knowledge to understand theoretical phenomena, and practical experiences, of application in the development of hardware and simulation software in industrial projects with needs of both the space segment (telecommunication, navigation, earth observation and space sciences ), as well as wireless terrestrial communications systems, whether wireless fixed as mobile.\n\nMicrowave engineering provides key tools to face technological challenges such as the design of radio frequency components and subsystems, for both terminal equipment and radio communications base stations. Requirements and technologies, factors for miniaturization.\n\nThe more detailed objectives are presented in the following list, so we consider that the student at the end of the course will be able to:\n\nUse tools for analysis and synthesis of devices and subsystems in the radio frequency and microwave bands, as well as to introduce the most widely used technologies in high frequency.\nManage the formulation of scattering parameters as a tool for synthesis and analysis of devices in high frequency. As well as the fundamental properties.\nAnalyze and design passive devices of n-ports, by means of the techniques provided, present in a RF-FEM (Radio Frequency-Front End Module): attenuators, dividers, couplers, resonators, modulators.\nDesign linear and nonlinear devices based on active elements (switch, limiters, mixers, amplifiers)\nExpress the conclusions of the work in the appropriate technical language.\n\nCompetences\nCommunication\nDevelop personal attitude.\nDevelop thinking habits.\nDraft, develop and sign projects in the field of telecommunications engineering that, depending on the speciality, are aimed at the conception, development or exploitation of telecommunication and electronic networks, services and applications.\nLearn new methods and technologies, building on basic technological knowledge, to be able to adapt to new situations.\nSelect and devise communication circuits, subsystems and systems that are guided or non-guided by electromagnetic, radiofrequency or optical means to fulfil certain specifications.\nLearning Outcomes\nAnalyse and design radiofrequency, microwave, broadcasting, radio-link and radio-determination antennas, circuits, subsystems and systems.\nCommunicate efficiently, orally and in writing, knowledge, results and skills, both professionally and to non-expert audiences.\nDesign radio communication based applications, understood to be systems for receiving and transporting information.\nDevelop curiosity and creativity.\nDevelop systemic thinking.\nDevelop the capacity for analysis and synthesis.\nGenerate innovative and competitive proposals in professional activity.\nManage information by critically incorporating the innovations of one's professional field, and analysing future trends.\nUse specific simulation tools to analyse and design radiofrequency telecommunication applications.\n\nContent\n1. TRANSMISSION LINE.\n\n2. GEOMETRIES OF THE TRANSMISSION LINE.\n\nPlanar transmission line, STRIPLINE.\n\nPlanar transmission line, MICROSTRIP.\n\n 3. MATRIX REPRESENTATION MICROWAVE CIRCUITS. \n\nScattering parameters.\n\nRelationship between parameters s, z and y.\n\nProperties of the scattering matrix.\n\nParameters [s] in networks with symmetry plane.\n\nPower transfer gain. Voltage gain and scattering parameters.\n\nTwo ports passive networks.\n\nLossless passive networks.\n\nScattering parameter of transmission line.\n\n4. PASSIVE MICROWAVE CIRCUITS.\n\nAttenuators\n\nThree ports passive networks (i).\n\nCirculator\n\nResistive dividers.\n\nDividers using transmission lines\n\nWilkinson's divider.\n\nFour-port networks (directional coupler).\n\nHybrid of 90º.\n\nHybrid of 180º.\n\nGeneral applications\n\nOperation as phase detector.\n\nFour ports networks with coupled lines.\n\nAnalysis with edge coupling.\n\nMicrowave resonators" . . "Presential"@en . "FALSE" . . "Advanced signal processing and communications"@en . . "7.50" . "NA" . . "Presential"@en . "TRUE" . . "Fundamentals of information and communication engineering"@en . . "15" . "Interdisciplinary teaching of the basics of communications engineering, signal processing and space physics" . . "Presential"@en . "FALSE" . . "Wireless communications & signal processing"@en . . "6.0" . "no data" . . "Presential"@en . "TRUE" . . "Statistical analysis and signal processing"@en . . "6.0" . "https://sigarra.up.pt/fcup/en/ucurr_geral.ficha_uc_view?pv_ocorrencia_id=502172" . . "Presential"@en . "FALSE" . . "Optimal filtering"@en . . "6.0" . "The course illustrates the basic estimation and filtering methodologies. The student will be able to use the most important estimation techniques and to formulate and study optimization problem of different kinds.\n\n\nSpecific objectives\n\n- Knowledge and understanding\nThe student will learn the estimation and filtering methodologies for being applied to different frameworks.\n\n- Use knowledge and understanding\nThe student will be able to formulate an estimation problem and design the optimal estimate, by implementing it to evaluate the consequent results\n\n- Communication skills\nThe course will allow the student to communicate and share the main problems in specific application fields, by focusing on the possible design procedures and evaluating their strength or weakness\n\n- Learning skills\nThe course will empower the analytical skills of the student, from the problem analysis to the study of the available scientific literature and down to the design and implementation." . . "Presential"@en . "TRUE" . . "Systems and signals"@en . . "6.0" . "Prerequisites\nBasic concepts of linear algebra and mathematical analysis.\n\nObjectives\nThe course introduces the elementary theoretical and practical basis of discrete-time and continuous time Signals and Systems. Particular emphasis is placed on the frequency representations common in signal processing applications, the continous-to-discrete time conversion, and the analysis of linear and invariant dynamical systems.\n\nProgram\n1. Basic concepts of discrete-time (dt) and continous-time (ct) signals. Examples. Transformations. 2. Basic conceps of systems. Memory, causalility, invariance, linearity, stability, invertibility. 3. Linear and time-invariant (LTI) systems. Impulse response. Convolution. Properties. 4. Laplace transform (LT). Transfer function (TF). LTI systems described by differential equations, poles and zeros. Relation between the TF and properties of LTI systems. Inverse LT and unilateral LT. 5. Fourier transform (FT) of tc signals. Representation of aperiodic signals via FT. Frequency response, filtering. Relation with the Fourier Series (FS) for periodic signals. 6. Fourier transform of td signals. Spectra of td signals. LTI systems described by difference equations. 7. Sampling. Discrete-time processing of continuous-time signals. Sampling theorem. Aliasing.\n\nEvaluation Methodology\n50% continuous evaluation / 50% non-continuous evaluation\n\nCross-Competence Component\nWorking in group stimulates the development of collaboration skills, including assignment of different roles to group members, as well as oral and written communication.\n\nLaboratorial Component\nFive lab assignments (the first one will not be graded), where the students have the opportunity to experiment with real-world and synthetic signals that illustrate the concepts conveyed in the lectures. Students work in groups of three and should submit one report for each graded assignment (moodle submission).\n\nProgramming and Computing Component\nElementary programming in Matlab for signal analysis and simulation of simple dynamical systems.\n\n\nMore information at: https://fenix.tecnico.ulisboa.pt/cursos/lerc/disciplina-curricular/845953938490013" . . "Presential"@en . "TRUE" . . "Digital signal processing"@en . . "20.0" . "DIGITAL SIGNAL PROCESSING ENG5027\nAcademic Session: 2023-24\nSchool: School of Engineering\nCredits: 20\nLevel: Level 5 (SCQF level 11)\nTypically Offered: Semester 1\nAvailable to Visiting Students: Yes\nShort Description\nThis course introduces the basic concepts and techniques of digital signal processing (DSP) and demonstrates some interesting and useful practical applications of DSP. It also provides practical experience in using Python in analysis and design of DSP systems and algorithms.\n\nTimetable\nFour lectures per week. Plus supporting Tutorials and Laboratory sessions.\n\nExcluded Courses\nNone\n\nCo-requisites\nNone\n\nAssessment\n70% Written Exam\n\n30% Lab report\n\nMain Assessment In: December\n\nCourse Aims\nThe aims of this course are to:\n\n■ introduce the basic concepts and techniques of digital signal processing (DSP);\n\n■ demonstrate some interesting and useful practical applications of DSP;\n\n■ provide practical experience in using DSP software in analysis and design of DSP systems and algorithms.\n\n■ design, implement, critically evaluate and benchmark an interdisciplinary DSP task\n\nIntended Learning Outcomes of Course\nBy the end of this course students will be able to:\n\n■ use the Fourier transform to filter signals from different application domain and critically evaluate them in the context of the application\n\n■ design FIR filters from a desired frequency response and evaluate their performance in the light of the intended application\n\n■ design IIR filters for low latency applications and evaluate them in terms of stability and latency introduced in the specific application.\n\n■ design matched filters for medical and communication situations and being able to benchmark the filters for their given application\n\n■ optimise filters for best performance;\n\n■ use Python as a filter design tool and knowing about its limitations and risks\n\n■ write object oriented DSP filter code in Python which can be used in production\n\n■ acquire interdisciplinary knowledge to provide a solution to a DSP problem and able to critically evaluate it\n\nMinimum Requirement for Award of Credits\nStudents must attend the degree examination and submit at least 75% by weight of the other components of the course's summative assessment.\n\n \n\nStudents must attend the timetabled laboratory classes.\n\n\nMore information at: https://www.gla.ac.uk/postgraduate/taught/sensorandimagingsystems/?card=course&code=ENG5027" . . "Presential"@en . "FALSE" . . "Signal Processing"@en . . . . . . . . . . . . . . . . . . . . . . . .