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Strumenti personali

DECISION, ESTIMATION AND DISTRIBUTED SENSING TECHNIQUES

Academic year and teacher
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Versione italiana
Academic year
2021/2022
Teacher
ANDREA CONTI
Credits
6
Didactic period
Secondo Semestre
SSD
ING-INF/03

Training objectives

The course aims to provide techniques and methodologies for cognitive and adaptive systems to take better decisions as well as to estimate contextual data from measurements gathered by distributed sensors.

The main knowledge obtained regards: distributed sensing; decision techniques based on binary and multiple hypotheses; estimation of parameters, contextual information, and intervals; regression techniques; model order selection; and principal component analysis of measured data. The teaching approach is application-driven with examples from a variety of engineering areas, including wireless sensor networks, localization systems, physical behavior analysis, and cognitive radio.

At the end of the course, the student will be able to apply statistical inference techniques to the design of context-aware cognitive systems.

Prerequisites

Basics knowledge from probability theory and statistics.

Course programme

The course consists of 60 hours of frontal lessons on:
- Recalling of probability theory and statistical inference
- Decision theory, multiple hypotheses and exercises
- Point processes and distributed sensing
- Estimation theory, regression, and exercises
- Model order selection
- Principal component analysis
- Applications

Didactic methods

The course consists in lessons from the instructor in class for all the arguments. For each argument theory will be followed by exercises. Additional exercises will be offered for individual study.

The material for the students is also available in English.

Learning assessment procedures

The examination is organized to allow the verification of knowledge learning with respect to the course program.

The examination consists in a written and in an oral part.
- The written part is related to an exercise with multiple questions on techniques for decision, estimation, and distributed sensing.
The kind of exercise is similar to those solved together with the instructor.
- The oral part consists of two questions spanning over the topics of the course.

The two parts are sustained in the same day, and the oral part can be accessed only if the written part is considered sufficient.
The final score accounts for both written and oral part.

The exam can be done in English.

The positive outcome of the examination shows the acquisition of knowledge and abilities specified in the course objectives.

Reference texts

Part of the material presented and that related to examples are provided by the instructor.

The following textbooks are suggested: TBD