TTIT47	Mathematical models, 10,5 ECTS-points /Tema 2: Matematiska modeller/ Advancement level: B
	Aim: To understand the principles of data- and control abstraction and ability to apply them for building models and simulating reality. Knowledge about modeling and processing of stochastic signals. Ability to analyze systems with stochastic inputs and basic understanding for time-discrete linear systems. Prerequisites: Mathematics from year 1. Linear systems from theme 1, semester 2. Computer science from theme 1 and 3 semester 3. Course organization: See the study handbook. Course content: The programming language SCHEME. Abstraction and definitions of functions. Recursive data structures. Recursion. Higher-order functions. Streams. Applications from statistics and linear systems. Examples of structures with complex data. Symbolic computations. Descriptions of general stochastic signals continuous in time; stationarity; ergodicity, mean values, effect, auto-correlation functions, spectral density. Linear filtering of stochastic signals, and orientation about non-linear filtering. Introduction to linear time-discrete systems. Course literature: See literature list.
TEN1	Written examination, 3 p.
UPG1	Written examination, 0 p.
UPG2	Written examination, 4 p.

Course language is swedish.