Information Theory
Teoria Transmiterii Informației
Course Description: This course aims to provide basic knowledge on introduction to mathematics of information theory. We will cover both classical and modern topics, including information entropy, lossless data compression, binary hypothesis testing, channel coding, and lossy data compression. The course offers an introduction to the quantitative theory of information and its applications to reliable, efficient communication systems. Topics include mathematical definition and properties of information, source coding theorem, lossless compression of data, optimal lossless coding, noisy communication channels, channel coding theorem, the source channel separation theorem, multiple access channels, broadcast channels,
Gaussian noise, and time-varying channels.
Course Outcomes: Students are expected to be able to Measure information and compute entropy; Understand and compute mutual information and channel capacity; Understand the limits of source coding and reliable communication; Encode and decode linear block codes using generator matrices and polynomials; Encode and decode convolutional codes using linear algebra and the Viterbi algorithm.
Home Automation
Course Description: *
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Analog Integrated Circuit - laboratory
Module Description: This module focuses on the study of analog integrated circuits with an emphasis to develop operational amplifiers and their applications. As part of the lab course, students will build analog systems using analog ICs and study their macro models, characteristics and limitations having as a support the Analog System Lab Kit PRO (ASLK PRO) .
Module Outcomes: Students should be able to:
understand the characteristics and specification of analog ICs used in electronic systems
develop a macromodel for an IC based on its terminal characteristics, I/O characteristics, DC-transfer characteristics, frequency response, stability characteristic and sensitivity characteristic.
make the right choice for an IC for a given application.
make the right choice for an IC for a given application
Computer Aided Graphics
Grafică Asistată de Calculator
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Course Outcomes: *
Digital Signal Processing - laboratory
Prelucrarea Digitală a Semnalelor
Module Description: This module provides knowledge on concepts of signals, systems, and signal processing, based on fundamental principles. The laboratories contain basic knowledge and mathematics, complemented by many examples. The laboratories cover the theory of digital signal processing techniques and digital filter design.
Module Outcomes: Students should be able to:
Recognize the differences between analog and digital signal processing and explain the key advantages of digital over analog processing.
Understand the interaction between signals and systems to the extent that we can adequately predict the effect of a system upon the input signal.
Understand the use and implications of the various properties of the discrete-time Fourier transform.
Understand the important types of allpass and minimum-phase systems and their use in theoretical investigations and practical applications.
Understand the major implication of sampling theory which is that it makes possible the processing of continuous-time signals using discrete-time signal processing techniques.
Understand the meaning and basic properties of DFT.
Develop and analyze practically useful structures for both FIR and IIR systems.
Design of discrete-time FIR and IIR filters.
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