Signal and Image Processing (курсова робота)

Major: Computer Engineering
Code of subject: 6.123.03.E.284
Credits: 2.00
Department: Specialized Computer Systems
Lecturer: Associate Professor Yevhenii Vavruk
Semester: 7 семестр
Mode of study: денна
Learning outcomes: As a result of studying the academic discipline, the student of education should be capable demonstrate the following learning outcomes: 1. Know the theoretical foundations of using algorithms. 2. Know the architecture and technical and structural characteristics of modern DSP and FPGAs. 3. Be able to calculate the main parameters of nodes. 4. Be able to choose microprocessor components to ensure the specified technical characteristics when designing nodes. 5. Be able to choose and master the skills of using software environments for the development of software for nodes.
Required prior and related subjects: Algorithms and calculation methods Parallel and distributed computing Modeling of computer systems Reconfigured computers Specialized microprocessor systems Methods, tools and technologies of designing computer systems Architecture of specialized computer systems
Summary of the subject: As a result of the study of the academic discipline, the student will gain knowledge of the theoretical foundations for the selection and use of hardware and software tools for signal and image processing, will acquire the ability to calculate the main characteristics of signal and image processing nodes, design a block diagram of algorithm execution, a functional diagram of an node, will acquire the ability to use typical hardware -software development and debugging tools for the design of nodes, get acquainted with various software development tools and master the integrated environment for designing the software of a given node.
Assessment methods and criteria: To assess students' knowledge, a credit control is provided, which consists of a written component - the correctness and reliability of the results obtained and the preparation (50 points) and an oral component (50 points).
Recommended books: 1. Ваврук Є. Я. Алгоритми та засоби обробки сигналів: навчальний посібник / Є. Я. Ваврук, О. Л. Лашко, Р. Б. Попович. – Львів: Видавництво «Сполом», 2021. – 240 c. 2. Тотосько О.В. Цифрова обробка сигналів та зображень : навчальний посібник / О.В. Тотосько , П.Д. Стухляк. - Тернопіль : ТНТУ імені Івана Пулюя, 2016. - 132 с. 3. Є. Ваврук , Р. Попович Цифрове опрацювання сигналів та зображень: Алгоритми та реалізація. Навчальний посібник з дисципліни „Проектування комп’ютерних засобів обробки сигналів та зображень” для студентів спеціальностей 7.091501 і 8.091501 "Комп'ютерні системи та мережі", 7.091503 і 8.091503 “Спеціалізовані комп'ютерні системи“ – Львів: Національний університет “Львівська політехніка”, 2008, 147 с. 4. . Є. Ваврук , О. Лашко Основи обробки сигналів Навчальний посібник з дисципліни “Цифрова обробка сигналів” для студентів базового напряму 6.0915 - “Комп’ютерна інженерія” Вид-во Нац. ун-ту “Львівська політехніка”, 2009 р. 104с. 5. Є. Ваврук, О. Лашко Програмування алгоритмів швидкого перетворення Фур’є//Методичні вказівки до курсовоої роботи 6. Є. Ваврук, О. Лашко Проектування процесора швидкого перетворення Фур’є//Методичні вказівки до курсової роботи. 7. Є.Ваврук, О.Акимишин Проектування процесора швидкого перетворення Фур’є на програмованих логічних інтегральних схемах//Методичні вказівки до курсової роботи.

Signal and Image Processing

Major: Computer Engineering
Code of subject: 6.123.03.E.110
Credits: 5.00
Department: Specialized Computer Systems
Lecturer: Associate Professor Yevhenii Vavruk
Semester: 7 семестр
Mode of study: денна
Learning outcomes: know the basic concepts of digital signal processing; • to have the terminology applicable in this field; • distinguish approaches to building systems for collecting, transforming, displaying, processing, storing and transmitting data; • to know the main operations of the DSP; • be able to apply the key algorithms of DSP; • use software environments for research and creation of models, which are necessary in the DSP; • be able to correlate the obtained results with the set goal.
Required prior and related subjects: Mathematical Analysis, Basics of discrete mathematics, Basics of algorithms and programming.
Summary of the subject: This discipline is intended for students to master the basic mathematical models and information characteristics of signals used in the study of data collection, transformation, processing, storage and transmission systems. For this, it is necessary to study the basic methods and algorithms of digital signal and image processing, to acquire theoretical knowledge and practical skills, which are also available for performing design work in the field of application of signal processing algorithms.In order to achieve program learning outcomes, the mathematical foundations of one-dimensional and two-dimensional signal processing and key algorithms for their processing are studied. The methods of discretization, compression, and filtering of signals and the tools that implement them are presented in a logical order, according to the sequence of use in general systems. The presentation of the theoretical material is divided into three logical blocks: the first part deals with signals and their properties; in the second - linear discrete systems, in particular, digital filters; in the third – digital images and their processing technologies.To acquire practical skills, a cycle of laboratory classes is offered, which involves familiarization with the SCILAB package and using its capabilities for signal and image processing.
Assessment methods and criteria: Assessment of students' knowledge is carried out in accordance with the work curriculum in the form of a semester control, which is carried out at the end of the semester and includes the results of the current control of students' knowledge, which is assessed for the performance of laboratory work, and a control measure - the answer to the corresponding exam ticket. The control measure is a mandatory type of control and is conducted in written and oral form at the end of the semester. Control questions are divided into: a) simple test tasks - yes/no choice; b) intermediate-level test tasks - a choice from several options; c) higher-level test tasks - solving problems with a numerical solution; d) the task of a complete written solution - the solution of the given task.
Recommended books: 1.Алгоритми та засоби обробки сигналів: навчальний посібник / Є. Я. Ваврук, О. Л. Лашко, Р. Б. Попович. – Львів: Видавництво «Сполом», 2021. – 240 c. 2.Солонина А.И. Основи цифровой обработки сигналов. 2-е издание. Учебное пособие–БХВ-Петербург, 2005.-753с 3.Айфичер, Эммануил С., Джервис, Барри У. Цифровая обработка сигналов: практический поход, 2-е изд.: Пер. с англ. – М.: Издательский дом “Вильямс”, 2004. – 992с.