AAT B4
Description
Evaluate the accuracy of a solution, pointing out errors and verifying its practicality, orders of magnitude and coherence in relation to the initial hypothesis.
Progression
M1 ():
M2 ():
M3 ():
AAv List (127)
P1ABALR-AAv1 (8H): At the end of the 1st semester, students are able to execute step by step algorithms comprising variables, conditional, iterative structures and function calls and in determine their results without error
P1ABALR-AAv3 (12H): At the end of the 1st semester, students must be able to verify the validity of an algorithm (it performs exactly the task for which it was designed) and its robustness (it is protected from abnormal conditions of use)
P1ACELE-AAv3 (72H): At the end of semester 1, students will be able to solve a given problem on a diagram they have never seen before, using the method of their choice if it is not imposed. The student will be able to determine the literal expression of any electrical quantity in a circuit as a function of its components. The student will be able to determine the operating point of a combination of dipoles operating in continuous operation, both graphically and analytically. To adapt to complex dipole structures not previously seen, they will use Thevenin/Norton modeling to represent the active dipole(s) of the combination before putting it into an equation. They will be able to evaluate power exchanges between receivers and generators, explaining their reasoning and justifying their results.
P2PZZGN-AAv2 (14H): At the end of ZG2, the group of students is able to correctly measure and identify the influence of physical parameters (Electronics: R , L, C - Mechanics: k, m, lambda) on the response of the system (damping, pseudo-period and natural frequency) of the 2nd order in two different ways: using simulation software OR physically with experimental models to be built . All the measurements and simulation results will be summarized in a document to be completed.
P2PZZGN-AAv6 (7H): At the end of the first week of ZG2 the student will be able with their PC, in a few minutes, to produce, manipulate or display time series described in CSV format, by writing a Python program which is inspired by the examples provided and respects the coding standards of the S2-IPI course.
P3ABELE-Aav1 (30H): At the end of the semester, an S3 student will be able to explain the operation of a given circuit containing diodes, bipolar or field-effect transistors, optocouplers, operational amplifiers, make hypotheses about the operation of non-linear elements, and verify them by calculating circuit currents and voltages and/or LTSpice simulation, determine input-output relations analytically and verify them by LTSpice simulation.
P3ABELE-Aav2 (15H): At the end of the semester, an S3 student will be able to identify the essential characteristics of an ADC and a DAC (quantum, full scale, conversion time).
P3ACCEL-AAv2 (53H): At the end of the semester the student has created from a microcontroller and elementary electronic components (resistors, capacitors, diodes, transistors, LEDs, potentiometers) at least one multitasking project described by specifications.
P4PZZGN-AAv2 (60H): On the basis of working hypotheses, the student can solve the problem posed and validate each step;
P4PZZGN-AAv3 (5H): Correctly compare simulated, experimental and theoretical results.
P4PDTHE-AAv1 (13H): At the end of the semester, the S3 student will be able to calculate in detail the quantities of heat exchanged between systems according to their parameters and potential phase transitions and d deduce the evolution of their temperature as a function of time for a system with a homogeneous temperature.
P4PDTHE-AAv2 (13H): At the end of the semester, the S3 student will be able to calculate in detail the distribution of the 1D temperature in steady and transient regimes, in a solid subjected to conduction and/or external heat sources or exchanges.
P4PDTHE-AAv3 (13H): At the end of the semester, the S3 student will be able to calculate in detail the heat exchange coefficient of Newton's law of a forced conducto-convective system.
P5AASHI-AAv2 (20H): At the end of the human sciences course in semester 5, the student must be able to fully design a feasible action that responds to a societal or environmental need previously identified and to define the conditions for its success.
P5ABNUM-AAv1 (40H): at the end of this course, each student knows how to solve any differential problem using a numerical method and characterize the properties of this method.
P5ABSIG-AAv1 (4H): At the end of the semester, the student must be able to recognize usual continuous signals (gate, triangle, step, ramp, harmonic, exponential, impulse) and model them using an analytical expression.
P5ABSIG-AAv2 (4H): At the end of the semester, the student must be able to apply and identify transformations on the temporal representation of analog continuous signals (superposition, shift, scale transformation and amplitude).
P5ABSIG-AAv3 (50H): At the end of the semester, the student must be able to analyze the frequency content of continuous signals, composed of usual signals, using the Fourier transformation. This spectral analysis consists in particular of: (1) Manipulating the complex formalism of the Fourier transformation (positive and negative frequencies) and finding the real, physically interpretable form of the decomposition (amplitude, phase, energy spectra and power); (2) Identify whether the signal is more or less rich in low and high frequencies and make the connection with its temporal form; (3) Determine the decay rate of the spectrum; (4) Identify particular frequencies according to the nature of the spectrum (discrete/continuous); (5) Determine spectrally (and temporally) the mean value, rms value, energy and power of the signal; (6) Determine the percentage of signal energy or power located in a given frequency band; (7) Synthesize a real signal by imposing a percentage of its total average power. The student will have consulted and assimilated the scientific resources necessary to complete the work to be carried out.
P5ABSIG-AAv4 (8H): At the end of the semester, the student must be able to analyze using a spectrum analyzer the frequency content of usual signals and real signals in sensor output. The student will have consulted and assimilated the scientific resources necessary to complete the work to be carried out.
P5ABSIG-AAv5 (12H): At the end of the semester, the student must be able to predict the response of a SLIT system (continuous, linear and time invariant system) to a model input ( combination of usual signals) using temporal convolution, or frequency filtering.
P5ABSIG-AAv6 (12H): At the end of the semester, the student must be able to carry out the temporal and frequency analysis of signals at the input and output of a continuous system of convolution-filtering (SLIT) and make the link with the frequency response and the amplitude and phase distortions of such a system. Analyzing here means in particular: (1) Making the link between the impulse response of a SLIT and its bandwidth; (2) Determine the amplitude and phase distortion, phase delay and group delay of classical transfer functions of order 1 and 2.
P5ADASA-AAV2 (20H): Closed-loop system analysis: By the end of the semester, students will be able to:
P5ADASA-AAV3 (20H): Frequency synthesis of linear controllers. By the end of the semester, students will be able to:
P5ODALG-AAv1 (6H): At the end of the programming course, a fifth semester student will be able to execute step by step algorithms comprising variables, conditional, iterative structures and function calls and determine their results without error
P5ODALG-AAv3 (8H): At the end of the programming course, a fifth semester student will be able to verify the validity of an algorithm (he carries out exactly the task for which he been designed) and its robustness (it is protected from abnormal conditions of use)
P5OFSIA-AAv1 (4H): At the end of the semester, the student must be able to recognize usual continuous signals (gate, triangle, step, ramp, harmonic, exponential, impulse) and model them by an analytical expression.
P5OFSIA-AAv2 (4H): At the end of the semester, the student must be able to apply and identify transformations on the temporal representation of analog continuous signals (superposition, shift, scale transformation and amplitude).
P5OFSIA-AAv3 (50H): At the end of the semester, the student must be able to analyze the frequency content of continuous signals, composed of usual signals, using the Fourier transformation. This spectral analysis consists in particular of: (1) Manipulating the complex formalism of the Fourier transformation (positive and negative frequencies) and finding the real, physically interpretable form of the decomposition (amplitude, phase, energy spectra and power); (2) Identify whether the signal is more or less rich in low and high frequencies and make the connection with its temporal form; (3) Determine the decay rate of the spectrum; (4) Identify particular frequencies according to the nature of the spectrum (discrete/continuous); (5) Determine spectrally (and temporally) the mean value, rms value, energy and power of the signal; (6) Determine the percentage of signal energy or power located in a given frequency band; (7) Synthesize a real signal by imposing a percentage of its total average power. The student will have consulted and assimilated the scientific resources necessary to complete the work to be carried out.
P5OFSIA-AAv4 (8H): At the end of the semester, the student must be able to analyze the frequency content of usual signals and real signals using a spectrum analyzer at the sensor output. The student will have consulted and assimilated the scientific resources necessary to complete the work to be carried out.
P5OFSIA-AAv5 (12H): At the end of the semester, the student must be able to predict the response of a SLIT system (continuous, linear and time invariant system) to a model input (combination of usual signals) using temporal convolution, or frequency filtering.
P5OFSIA-AAv6 (12H): At the end of the semester, the student must be able to carry out the temporal and frequency analysis of signals at the input and output of a continuous system of convolution-filtering (SLIT) and make the link with the frequency response and the amplitude and phase distortions of such a system. Analyzing here means in particular: (1) Making the link between the impulse response of a SLIT and its bandwidth; (2) Determine the amplitude and phase distortion, phase delay and group delay of classical transfer functions of order 1 and 2.
P5OFASA-AAV2 (20H): Closed-loop system analysis: By the end of the semester, students will be able to:
P5OFASA-AAV3 (20H): Frequency synthesis of linear controllers. By the end of the semester, students will be able to:
P6AASHI-AAv3 (10H): At the end of the Humanities course in semester 6, students should be able to think critically to evaluate solutions (by seeking alternatives to proposed choices, comparing documents and/or points of view, producing different representations of a problem, and identifying the strengths and weaknesses of a solution) and to position/choose using epistemological and ethical tools.
P6ABDSM-AAv1 (20H): By the end of the semester, S6 students will be able to carry out a detailed design of a beam in a dynamic vibration framework.
P6ABDSM-AAv2 (20H): By the end of the semester, the S6 student will be able to design mechanical systems involving deformable objects, with the aim of addressing problems encountered by structural engineers. The approaches adopted include the use of advanced numerical tools and enable the optimisation of the behaviour of these objects by adjusting various parameters such as their geometry or physical properties.
P6ADADD-AAV1 (0H): At the end of the data analysis course, students will be able to choose, and justify their choice, a parametric distribution to model a given dataset and estimate its parameter(s) by constructing confidence intervals, while being able to explain the meaning and scope of these estimates.
P6ADADD-AAV2 (0H): At the end of the data analysis course, students will be able to construct hypothesis tests (in the contexts of p-value, ANOVA, MANOVA, etc.) and calculate the associated statistics to draw conclusions about the data sets provided. In addition, students will be able to explain the scope and validity of the conclusions.
P6ADADD-AAV6 (0H): At the end of the data analysis course, students will be able to analyze the quality of a model built using the methods taught in the course.
P6ADSIG-AAv1 (3H): At the end of the semester, the student should be able to establish the analytical expression of discrete-time signals and systems (this course is limited to the case of regular sampling).
P6ADSIG-AAv2 (9H): At the end of the semester, the student should be able to perform the spectral analysis of sampled signals and systems (discrete-time and continuous-frequency analysis) based on the concept of the Fourier transform in the sense of distributions.
P6ADSIG-AAv3 (13H): At the end of the semester, the student must be able to analyse and design a digitisation-reconstruction chain for an analogue DC signal. The digital signal processing concepts to be put into practice are in particular : (1) Shannon's theorem on the choice of sampling frequency (oversampling and undersampling) and the spectral properties derived from it; (2) Issues on the choice of anti-aliasing filter parameters to be able to minimise overlap noise; (3) The issues involved in choosing the quantisation method and the number of digitiser bits to maximise the signal-to-noise ratio; (4) The issues involved in choosing the parameters of the low-pass reconstruction filter (interpolator filter) to correctly reproduce the analogue DC signal.
P6ADSIG-AAv5 (12H): At the end of the semester, the student must be able to carry out a complete analysis (time response, frequency response, stability study, number of coefficients in the recurrence equation, number of delay elements, fluence graph, digital sensitivity and calculation noise) of a digital filter of the RIF or RII type using discrete convolution and the Z transfer function.
P6OCNUM-AAv1 (30H): at the end of this course, each student will be able to solve any differential problem using a numerical method and to characterise the properties of this method. This solution and characterisation are satisfactory if:
P6OCYTHE-AAv1 (12.5H): At the end of the semester, S6O students will be able to calculate in detail the quantities of heat exchanged between systems or due to potential phase transitions and to deduce the evolution of their temperature as a function of time.
P6OCYTHE-AAv2 (12.5H): At the end of the semester, S6O students will be able to calculate in detail the steady-state temperature distribution in a solid subject to conduction and external heat sources or exchanges.
P6OESIN-AAv1 (3H): At the end of the semester, the student should be able to establish the analytical expression of discrete-time signals and systems (this course is limited to the case of regular sampling).
P6OESIN-AAv2 (9H): At the end of the semester, the student should be able to perform the spectral analysis of sampled signals and systems (discrete-time and continuous-frequency analysis) based on the concept of the Fourier transform in the sense of distributions.
P6OESIN-AAv3 (9H): At the end of the semester, students should be able to analyse and design a digitisation-reconstruction chain for continuous analogue signals. The digital signal processing concepts to be put into practice are in particular: (1) Shannon's theorem on the choice of sampling frequency (oversampling and undersampling) and the spectral properties derived from it; (2) The issues involved in choosing the parameters of the anti-aliasing filter to be able to minimise the overlapping noise; (3) The issues involved in choosing the parameters of the low-pass reconstruction filter (interpolator filter) to correctly reconstruct the analogue DC signal.
P6OESIN-AAv5 (12H): At the end of the semester, the student must be able to carry out a complete analysis (time response, frequency response, stability study, number of coefficients in the recurrence equation, number of delay elements, fluence graph, digital sensitivity and calculation noise) of a digital filter of the RIF or RII type using discrete convolution and the Z transfer function. This analysis should lead to an appropriate and argued choice with regard to the signal to be filtered.
P6PZZGN-AAv1 (25H): design the prototype of a non-mobile mechatronic system with two self-controlled axes
P6PZZGN-AAv3 (12H): set up a test protocol for a non-mobile mechatronic system with two self-controlled axes, implement it and evaluate the results
P6PASHI-AAv3 (10H): At the end of the Humanities course in semester 6, students should be able to think critically to evaluate solutions (by seeking alternatives to proposed choices, comparing documents and/or points of view, producing different representations of a problem, and identifying the strengths and weaknesses of a solution) and to position/choose using epistemological and ethical tools.
P6PBDSM-AAv1 (20H): By the end of the semester, S6 students will be able to carry out a detailed design of a beam in a dynamic vibration framework.
P6PBDSM-AAv2 (20H): By the end of the semester, the S6 student will be able to design mechanical systems involving deformable objects, with the aim of addressing problems encountered by structural engineers. The approaches adopted include the use of advanced numerical tools and enable the optimisation of the behaviour of these objects by adjusting various parameters such as their geometry or physical properties.
P6PDADD-AAV1 (0H): At the end of the data analysis course, students will be able to choose, and justify their choice, a parametric distribution to model a given dataset and estimate its parameter(s) by constructing confidence intervals, while being able to explain the meaning and scope of these estimates.
P6PDADD-AAV2 (0H): At the end of the data analysis course, students will be able to construct hypothesis tests (in the contexts of p-value, ANOVA, MANOVA, etc.) and calculate the associated statistics to draw conclusions about the data sets provided. In addition, students will be able to explain the scope and validity of the conclusions.
P6PDADD-AAV6 (0H): At the end of the data analysis course, students will be able to analyze the quality of a model built using the methods taught in the course.
P6PDSIG-AAv1 (3H): At the end of the semester, the student should be able to establish the analytical expression of discrete-time signals and systems (this course is limited to the case of regular sampling).
P6PDSIG-AAv2 (9H): At the end of the semester, the student should be able to perform the spectral analysis of sampled signals and systems (discrete-time and continuous-frequency analysis) based on the concept of the Fourier transform in the sense of distributions.
P6PDSIG-AAv3 (13H): At the end of the semester, the student must be able to analyse and design a digitisation-reconstruction chain for an analogue DC signal. The digital signal processing concepts to be put into practice are in particular : (1) Shannon's theorem on the choice of sampling frequency (oversampling and undersampling) and the spectral properties derived from it; (2) Issues on the choice of anti-aliasing filter parameters to be able to minimise overlap noise; (3) The issues involved in choosing the quantisation method and the number of digitiser bits to maximise the signal-to-noise ratio; (4) The issues involved in choosing the parameters of the low-pass reconstruction filter (interpolator filter) to correctly reproduce the analogue DC signal.
P6PDSIG-AAv5 (12H): At the end of the semester, the student must be able to carry out a complete analysis (time response, frequency response, stability study, number of coefficients in the recurrence equation, number of delay elements, fluence graph, digital sensitivity and calculation noise) of a digital filter of the RIF or RII type using discrete convolution and the Z transfer function.
P7MACE-AAv5 (12H): Comparison of experimental results with theoretical calculations or simulations. At the end of this course, the seventh semester student will be able, in a group of 4 to 5 students, to make the link between experimental data that they have produced and theoretical results obtained by calculation and/or numerical simulation.
P7MACE-AAv9 (13H): Modeling for the vector control of a synchronous motor. At the end of this course, the seventh semester student will be able, in pairs, to establish a model in order to implement the vector control of a synchronous motor, with current and speed controls. The development context will lead to mastery of rapid prototyping tools in order to switch from a simulated model to functional code for the target.
P7ETIM-AAv1 (12H): At the end of the semester, the student must be able to do the modeling and spectral analysis of real sampling mechanisms, in particular the averaging sampler (or tracker ) and the hold sampler (or hold). The student must know the influence of the choice between these two processes on the spectrum of the sampled signal and take it into account when designing the two filters, the guard filter (upstream of sampling) and the reconstruction filter or interpolator.
P7ETIM-AAv2 (6H): At the end of the semester, the student will be able to determine the correlation functions (intercorrelation, autocorrelation) and the spectral energy density (DSE) or power (DSP ) of deterministic signals. It must also be able to apply correlation in radar detection to detect the presence of a pattern in a received signal.
P7ETIM-AAv3 (12H): At the end of the semester, the student must be able to do the modeling and spectral analysis of the principles of modulation and demodulation of amplitude and frequency. The student must know how to analyze and interpret the temporal and frequency representations of analog signals corresponding to the following modulation formats: AM (dual band with DSB carrier, dual band with suppressed carrier DSB-SC, single sideband SSB) and FM (narrow band , wideband). He must also know how to use simulation tools (python, matlab or octave) and the spectrum analyzer to carry out demodulation by envelope detector or synchronous detector.
P7ETIM-AAv4 (28H): At the end of the semester, the student must be able to design, analyze and implement digital filters of type RII or RIF in response to specifications in a specification. To successfully complete this work, the student must be able to: (1) Translate the specifications into a template. (2) Appropriately choose a filter structure (RII or RIF) and a synthesis method (bilinear transformation, impulse invariance or transfer function sampling) by arguing the relevance of the choices made. (3) Determine the filter coefficients by direct calculation or using a matlab/simulink type rapid prototyping tool. (4) Implement the filter in an interpreted language such as Python, Matlab or Octave and validate its performance against the specified template. He must also be able to study the influence of the frequency distortion implied by the synthesis method. (5) Choose a form (direct, cascade or parallel) of implementation. It must also be able to study the influence of the frequency distortion implied by the quantification of the filter on a finite number of bits (sensitivity to the finite representation of the coefficients). (6) Implement the filter on a microcontroller or DSP type hardware target. (7) Validate the synthesis against the specifications by measurement using a spectrum analyzer.
P7ETIM-AAv6 (40H): At the end of the semester, the student will be familiar with the challenges of artificial vision and will have acquired the fundamental concepts of processing and analysis of digital images 2D. This concerns: (1) the representation of images in the spatial and frequency domain, (2) contrast improvement by histogram modification techniques (linear and non-linear anamorphosis), (3) denoising by techniques linear filtering (2D convolution operators) and non-linear (filtering of order statistics, image averaging, morphological transformations), (4) restoration by contrast enhancement operations (deblurring), (5) segmentation by contour-based and region-based approaches, (6) texture analysis by frequency and statistical approaches, (7) feature extraction using attribute selection tools, (8) recognition of objects by Hough transform and by machine learning algorithms.
P7RYEEA-AAv2 (23H): Introduction to digital communications. By the end of this part of the module, students will be able to analyse and design a simple digital transmission chain, taking into account a noisy channel (AWGN) and bandwidth constraints, and to evaluate its performance in terms of bit error rate (BER).
P7RYEEA-AAv5 (23H): Spectrum spreading and physical layer security. By the end of this section, students will be able to analyse spectrum spreading techniques and assess their role in the physical layer security of wireless communication systems.
P7RYEEA-AAv6 (23H): Multidimensional random signal processing and MIMO/DOA applications. By the end of this section, students will be able to apply the tools of multidimensional random signal processing to direction-of-arrival (DOA) estimation and the analysis of MIMO systems.
P7RYPHO-AAv2 (23H): Introduction to digital communications. By the end of this part of the module, students will be able to analyse and design a simple digital transmission chain, taking into account a noisy channel (AWGN) and bandwidth constraints, and to evaluate its performance in terms of bit error rate (BER).
P93PER-AAV2 (20H): At the end of the PER module, students must be able to draw up an analysis grid for a solution and evaluate its relevance with regard to environmental and societal issues
P91CNO-AAV1 (30H): The student of the CNO module, at the end of the module, will be able to describe the main elements (active and passive components) of the architecture of a WDM optical communication chain (from transmitter to receiver) and to use the main metrics, tools and methods to evaluate transmission quality.
P91CNO-AAV4 (20H): The student of the CNO module, at the end of the module, will be able to identify the different constituent blocks of a digital transmission chain (encoders, transmitters, receivers, propagation channel) and to know the role and main characteristics of each element. The student will be able to understand the importance of the concept of entropy in digital transmission and its link with the amount of information contained in a digital signal.
P91CNO-AAV5 (20H): The student of the CNO module, at the end of the module, will be able to master source coding techniques to compress information efficiently , using methods such as Huffman coding, arithmetic coding, Lempel-Ziv coding. The student will be able to understand how entropy can be used to optimize data compression and digital signal transmission. The student will be able to master different channel error detection and correction techniques, such as linear error correcting codes, Hamming codes, Reed-Solomon codes, etc.
P91CNO-AAV8 (15H): The student of the CNO module, at the end of the module, will be able to analyze, implement and study the performances (in EVM, SER, BER) of a simple single-carrier (M-QAM, M-PSK) or multi-carrier (CP-OFDM) digital communication chain for a Gaussian or selective additive channel in stationary frequency. The student will also be able to implement some classic algorithms at the receiver level using preamble and pilot symbols (carrier frequency offset correction, synchronization, zero-forcing equalization, linear LMS equalization).
P91MRA-AAv7 (18.75H): At the end of the semester, MRA students will be able to calculate the planar kinematic model of wheeled robots
P92CRF-AAv2 (23H): Introduction to digital communications. By the end of this part of the module, students will be able to analyse and design a simple digital transmission chain, taking into account a noisy channel (AWGN) and bandwidth constraints, and to evaluate its performance in terms of bit error rate (BER).
P92CRF-AAv5 (23H): Spectrum spreading and physical layer security. By the end of this section, students will be able to analyse spectrum spreading techniques and assess their role in the physical layer security of wireless communication systems.
P92CRF-AAv6 (23H): Multidimensional random signal processing and MIMO/DOA applications. By the end of this section, students will be able to apply the tools of multidimensional random signal processing to direction-of-arrival (DOA) estimation and the analysis of MIMO systems.
P95CCM-AAV3 (12H): At the end of this course, the student will be able to build a state observer and synthesize a state feedback control observed on a SISO linear system meeting specifications (stability, precision, speed, robustness).
P95CCM-AAV4 (12H): At the end of this course, the student will be able to model the uncertainties of modeling a discrete-time dynamic system and the uncertainties observation of the state of the system, with a view to an adaptive estimation of the state which it will carry out by Kalman filtering for the case of linear systems.
P95CCM-AAV5 (20H): At the end of this course, the student will be able to linearize a dynamic process or an observation law in order to carry out an adaptive state estimation by extended Kalman filtering (EKF filter) and perform a comparison with an Unscented Kalman filter (UKF).
P95CCM-AAV6 (16H): At the end of this course, the student will be able to control a linear system by feedback state according to a quadratic optimization criterion: LQR command or LQG command when the state is only partially observed
P95CCM-AAV8 (42H): At the end of this course, the student will be able to implement, set up and adjust some system control solutions non-linear: linearizing control, control by flatness, control by Lyapunov function,…
P10STA-AAv3 (150H): At the end of the engineering internship, the student is able to adapt a mathematical or other model to the problem to be solved, to use reasoning and formal calculation techniques and digital views in progress in order to solve the problem theoretically or by simulation and evaluate the accuracy of the related concrete solution.
P5ODALG-AAv1 (6H): At the end of the programming course, a fifth semester student will be able to execute step by step algorithms comprising variables, conditional, iterative structures and function calls and determine their results without error
P5ODALG-AAv3 (8H): At the end of the programming course, a fifth semester student will be able to verify the validity of an algorithm (he carries out exactly the task for which he been designed) and its robustness (it is protected from abnormal conditions of use)
P5OFSIA-AAv1 (4H): At the end of the semester, the student must be able to recognize usual continuous signals (gate, triangle, step, ramp, harmonic, exponential, impulse) and model them by an analytical expression.
P5OFSIA-AAv2 (4H): At the end of the semester, the student must be able to apply and identify transformations on the temporal representation of analog continuous signals (superposition, shift, scale transformation and amplitude).
P5OFSIA-AAv3 (50H): At the end of the semester, the student must be able to analyze the frequency content of continuous signals, composed of usual signals, using the Fourier transformation. This spectral analysis consists in particular of: (1) Manipulating the complex formalism of the Fourier transformation (positive and negative frequencies) and finding the real, physically interpretable form of the decomposition (amplitude, phase, energy spectra and power); (2) Identify whether the signal is more or less rich in low and high frequencies and make the connection with its temporal form; (3) Determine the decay rate of the spectrum; (4) Identify particular frequencies according to the nature of the spectrum (discrete/continuous); (5) Determine spectrally (and temporally) the mean value, rms value, energy and power of the signal; (6) Determine the percentage of signal energy or power located in a given frequency band; (7) Synthesize a real signal by imposing a percentage of its total average power. The student will have consulted and assimilated the scientific resources necessary to complete the work to be carried out.
P5OFSIA-AAv4 (8H): At the end of the semester, the student must be able to analyze the frequency content of usual signals and real signals using a spectrum analyzer at the sensor output. The student will have consulted and assimilated the scientific resources necessary to complete the work to be carried out.
P5OFSIA-AAv5 (12H): At the end of the semester, the student must be able to predict the response of a SLIT system (continuous, linear and time invariant system) to a model input (combination of usual signals) using temporal convolution, or frequency filtering.
P5OFSIA-AAv6 (12H): At the end of the semester, the student must be able to carry out the temporal and frequency analysis of signals at the input and output of a continuous system of convolution-filtering (SLIT) and make the link with the frequency response and the amplitude and phase distortions of such a system. Analyzing here means in particular: (1) Making the link between the impulse response of a SLIT and its bandwidth; (2) Determine the amplitude and phase distortion, phase delay and group delay of classical transfer functions of order 1 and 2.
P5OFASA-AAV2 (20H): Closed-loop system analysis: By the end of the semester, students will be able to:
P5OFASA-AAV3 (20H): Frequency synthesis of linear controllers. By the end of the semester, students will be able to:
P6EASHI-AAv2 (10H): At the end of the humanities course, students must be able to design in full or present a feasible action that meets a previously identified societal or environmental need and define the conditions for its success.
P6ECNUM-AAv1 (30H): at the end of this course, each student will be able to solve any differential problem using a numerical method and to characterise the properties of this method. This solution and characterisation are satisfactory if:
P6EESIN-AAv1 (3H): At the end of the semester, the student should be able to establish the analytical expression of discrete-time signals and systems (this course is limited to the case of regular sampling).
P6EESIN-AAv2 (9H): At the end of the semester, the student should be able to perform the spectral analysis of sampled signals and systems (discrete-time and continuous-frequency analysis) based on the concept of the Fourier transform in the sense of distributions.
P6EESIN-AAv3 (9H): At the end of the semester, students should be able to analyse and design a digitisation-reconstruction chain for continuous analogue signals. The digital signal processing concepts to be put into practice are in particular: (1) Shannon's theorem on the choice of sampling frequency (oversampling and undersampling) and the spectral properties derived from it; (2) The issues involved in choosing the parameters of the anti-aliasing filter to be able to minimise the overlapping noise; (3) The issues involved in choosing the parameters of the low-pass reconstruction filter (interpolator filter) to correctly reconstruct the analogue DC signal.
P6EESIN-AAv5 (12H): At the end of the semester, the student must be able to carry out a complete analysis (time response, frequency response, stability study, number of coefficients in the recurrence equation, number of delay elements, fluence graph, digital sensitivity and calculation noise) of a digital filter of the RIF or RII type using discrete convolution and the Z transfer function. This analysis should lead to an appropriate and argued choice with regard to the signal to be filtered.
P7EZZGN-AAv1 (25H): design the prototype of a non-mobile mechatronic system with two self-controlled axes
P7EZZGN-AAv3 (12H): set up a test protocol for a non-mobile mechatronic system with two self-controlled axes, implement it and evaluate the results
P7EBADD-AAV1 (0H): At the end of the data analysis course, students will be able to choose, and justify their choice, a parametric distribution to model a given dataset and estimate its parameter(s) by constructing confidence intervals, while being able to explain the meaning and scope of these estimates.
P7EBADD-AAV2 (0H): At the end of the data analysis course, students will be able to construct hypothesis tests (in the contexts of p-value, ANOVA, MANOVA, etc.) and calculate the associated statistics to draw conclusions about the data sets provided. In addition, students will be able to explain the scope and validity of the conclusions.
P7EBADD-AAV6 (0H): At the end of the data analysis course, students will be able to analyze the quality of a model built using the methods taught in the course.
P7ECACE-AAv5 (12H): Comparison of experimental results with theoretical calculations or simulations. At the end of this course, the seventh semester student will be able, in a group of 4 to 5 students, to make the link between experimental data that they have produced and theoretical results obtained by calculation and/or numerical simulation.
P7ECACE-AAv9 (13H): Modeling for the vector control of a synchronous motor. At the end of this course, the seventh semester student will be able, in pairs, to establish a model in order to implement the vector control of a synchronous motor, with current and speed controls. The development context will lead to mastery of rapid prototyping tools in order to switch from a simulated model to functional code for the target.
P7EEENT-AAv_B (0H): By the end of S7, students will be able to define scientific problems to solve, analyze them, model them and propose one or more solutions by making simplifying assumptions, using existing models and adapting them to the situation, and justifying their choices in an engineering domain.
P8EZZGN-AAv2 (21H): develop a real-time prototype of the synthesiser on a microcontroller target, integrate MIDI communication via USB, and experimentally validate its behaviour using the laboratory’s instrumentation
P8ECTIM-AAv1 (12H): At the end of the semester, the student must be able to do the modeling and spectral analysis of real sampling mechanisms, in particular the averaging sampler (or tracker ) and the hold sampler (or hold). The student must know the influence of the choice between these two processes on the spectrum of the sampled signal and take it into account when designing the two filters, the guard filter (upstream of sampling) and the reconstruction filter or interpolator.
P8ECTIM-AAv2 (6H): At the end of the semester, the student will be able to determine the correlation functions (intercorrelation, autocorrelation) and the spectral energy density (DSE) or power (DSP ) of deterministic signals. It must also be able to apply correlation in radar detection to detect the presence of a pattern in a received signal.
P8ECTIM-AAv3 (12H): At the end of the semester, the student must be able to do the modeling and spectral analysis of the principles of modulation and demodulation of amplitude and frequency. The student must know how to analyze and interpret the temporal and frequency representations of analog signals corresponding to the following modulation formats: AM (dual band with DSB carrier, dual band with suppressed carrier DSB-SC, single sideband SSB) and FM (narrow band , wideband). He must also know how to use simulation tools (python, matlab or octave) and the spectrum analyzer to carry out demodulation by envelope detector or synchronous detector.
P8ECTIM-AAv4 (28H): At the end of the semester, the student must be able to design, analyze and implement digital filters of type RII or RIF in response to specifications in a specification. To successfully complete this work, the student must be able to: (1) Translate the specifications into a template. (2) Appropriately choose a filter structure (RII or RIF) and a synthesis method (bilinear transformation, impulse invariance or transfer function sampling) by arguing the relevance of the choices made. (3) Determine the filter coefficients by direct calculation or using a matlab/simulink type rapid prototyping tool. (4) Implement the filter in an interpreted language such as Python, Matlab or Octave and validate its performance against the specified template. He must also be able to study the influence of the frequency distortion implied by the synthesis method. (5) Choose a form (direct, cascade or parallel) of implementation. It must also be able to study the influence of the frequency distortion implied by the quantification of the filter on a finite number of bits (sensitivity to the finite representation of the coefficients). (6) Implement the filter on a microcontroller or DSP type hardware target. (7) Validate the synthesis against the specifications by measurement using a spectrum analyzer.
P8ECTIM-AAv6 (40H): At the end of the semester, the student will be familiar with the challenges of artificial vision and will have acquired the fundamental concepts of processing and analysis of digital images 2D. This concerns: (1) the representation of images in the spatial and frequency domain, (2) contrast improvement by histogram modification techniques (linear and non-linear anamorphosis), (3) denoising by techniques linear filtering (2D convolution operators) and non-linear (filtering of order statistics, image averaging, morphological transformations), (4) restoration by contrast enhancement operations (deblurring), (5) segmentation by contour-based and region-based approaches, (6) texture analysis by frequency and statistical approaches, (7) feature extraction using attribute selection tools, (8) recognition of objects by Hough transform and by machine learning algorithms.
P8EEENT-AAv_B (0H): By the end of S8, students will be able to define scientific problems to solve, analyze them, model them and propose one or more solutions by adopting a research approach
S9FISEA_PER-AAv2 (20H): By the end of the PER module, students must be able to establish an analysis grid of a solution and evaluate its relevance regarding environmental and societal challenges
S9FISEA_CCM-AAv3 (12H): By the end of this course, students will be able to construct a state observer and synthesize an observed state feedback control on a linear SISO system meeting specifications (stability, precision, speed, robustness).
S9FISEA_CCM-AAv4 (12H): By the end of this course, students will be able to model modeling uncertainties of a discrete-time dynamic system and state observation uncertainties, for adaptive state estimation they will implement using Kalman filtering for linear systems.
S9FISEA_CCM-AAv5 (20H): By the end of this course, students will be able to linearize a dynamic process or observation law to perform adaptive state estimation using extended Kalman filtering (EKF filter) and make a comparison with an Unscented Kalman filter (UKF).
S9FISEA_CCM-AAv6 (16H): By the end of this course, students will be able to implement linear system control by state feedback according to a quadratic optimization criterion: LQR control or LQG control when the state is only partially observed
S9FISEA_CCM-AAv8 (42H): By the end of this course, students will be able to implement, deploy and tune some nonlinear system control solutions: linearizing control, flatness-based control, Lyapunov function-based control...
S9FISEA_ENT-AAv_B (0H): By the end of S9, students will be able to define scientific problems to solve, analyze them, model them and propose one or more robust solutions by adopting a rigorous research approach in a professional context.
S10FISEA_ENT-AAvB (0H): By the end of S10, students will be able to define scientific problems to solve, analyze them, _and, if applicable, model them and propose one or more robust solutions by adopting a rigorous research approach in a professional context.