Objectives of Programme's Learning Outcomes

• Imagine, implement and operate systems/solutions/software to deal with a complex problem in the field of electricity by integrating needs, contexts and issues (technical, economic, societal, ethical and environmental).
• Identify complex problems to be solved and formulate the specifications by integrating client needs, contexts and issues (technical, economic, societal, ethical and environmental).
• On the basis of modelling and experimentation, design one or more systems / one or more solutions / one or more software and/or hardware implementations responding to the problem posed; evaluate them taking into account the various parameters of the specifications.
• Implement a chosen system/solution/software/circuit in the form of a diagram, flow chart, algorithm, plan, model, prototype, program, software and/or digital model.
• Evaluate the approach and results for their adaptation (tests, measurements, optimisation and quality).
• Mobilise a structured set of scientific knowledge and skills and specialised techniques in order to carry out electrical engineering missions, using their expertise and adaptability.
• Master and mobilise knowledge, models, methods and techniques relating to the basics of electricity, electronics, automation, signal analysis and processing, telecommunications; modern electrical network engineering (production, transport, distribution); electric vehicles; advanced electronic systems; wired and wireless telecommunications; intelligent sensors; human-machine interfaces; mathematical modelling and analysis of dynamic systems; process control; image processing and processing; and the use of the Internet; advanced electronic systems; wired and wireless telecommunications; intelligent sensors; human-machine interfaces; mathematical modelling and analysis of dynamic systems; process control; image and sound processing and, more s
• Analyse and model a problem by critically selecting theories and methodological approaches (modelling, calculations), and taking into account multidisciplinary aspects.
• Identify and discuss possible applications of new and emerging technologies in the field of electrical engineering.
• Assess the validity of models and results in view of the state of science and characteristics of the problem.
• Plan, manage and lead projects in view of their objectives, resources and constraints, ensuring the quality of activities and deliverables.
• Define and align the project in view of its objectives, resources and constraints.
• Assess the approach and achievements, regulate them in view of the observations and feedback received.
• Respect deadlines and timescales
• Communicate and exchange information in a structured way - orally, graphically and in writing, in French and in one or more other languages - scientifically, culturally, technically and interpersonally, by adapting to the intended purpose and the relevant public.
• Use and produce high-quality scientific and technical papers (reports, plans, specifications, etc.), adapted particularly to the intended purpose and the relevant public.
• Master technical English in the field of electrical engineering.

Learning Outcomes of UE

understand the theory required for developing a library of basic digital signal processing components (sampling, convolution, filtering, poles and zeros in the z plane, FFT, sub-band analysis, autocorrelation estimators, power spectral density estimators);implement these components in PYTHON and create a digital signal processing system with PYTHON

UE Content: description and pedagogical relevance

linear time-invariant digital systems; frequency analysis of digital signals and systems; Shannon theorem and sampling theory; discrete (and Fast) Fourier Transform; spectral analysis of random signals; digital filters (including elements of digital filter synthesis); simple digital system in PYTHON

Prior Experience

Algebra of complex numbers

Type(s) and mode(s) of Q1 UE assessment

• Written examination - Face-to-face
• Production (written work, report, essay, collection, product, etc.) - To be submitted in class

Q1 UE Assessment Comments

Signal Processing 1 = 80% (of which Project = 35%; written exam = 65%)
Signal Processing 2 = 20% (of which project report = 100%)

Method of calculating the overall mark for the Q1 UE assessment

Signal Processing 1 = 80% (of which Project = 35%; written exam = 65%)
Signal Processing 2 = 20% (of which project report = 100%)

Type(s) and mode(s) of Q1 UE resit assessment (BAB1)

• N/A - Néant

Q1 UE Resit Assessment Comments (BAB1)

Not applicable

Method of calculating the overall mark for the Q1 UE resit assessment

not applicable

Type(s) and mode(s) of Q3 UE assessment

• Written examination - Face-to-face

Q3 UE Assessment Comments

A sigle written examen - exercicses only (100/100)
 

Method of calculating the overall mark for the Q3 UE assessment

A sigle written examen - exercicses only (100/100)