Objectives of Programme's Learning Outcomes

• Imagine, implement and operate systems/solutions/software to address a complex problem in the field of electrical engineering as a source of information 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).
• Based on modelling and experimentation, design one or more systems/solutions/software addressing the problem raised; evaluate them in light of various parameters of the specifications.
• Implement a chosen system/solution/software in the form of a drawing, a schema, a flowchart, an algorithm, a plan, a model, a prototype, 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 appropriately mobilise knowledge, models, methods and techniques specific to electrical engineering.
• 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

Content of UE

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 of Assessment for UE in Q1

• Presentation and/or works
• Written examination
• Practical test

Q1 UE Assessment Comments

Signal Processing 1 = 80% (of which Practicla test = 35%; writenexam = 65%)
Signal Processing 2 = 20% (of which project report = 100%)

Type of Assessment for UE in Q3

• Written examination

Q3 UE Assessment Comments

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

Type of Resit Assessment for UE in Q1 (BAB1)

• Written examination

Q1 UE Resit Assessment Comments (BAB1)

Not applicable