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Цифровая обработка сигналов Часть 2. Дискретные и цифровые фильтры

Сергиенко Александр Борисович
Курс разработан Санкт-Петербургским государственным электротехническим университетом «ЛЭТИ» им. В.И. Ульянова при поддержке Санкт-Петербургского политехнического университета Петра Великого. «Дискретные и цифровые фильтры» — второй курс специализации,...
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Курс разработан Санкт-Петербургским государственным электротехническим университетом «ЛЭТИ» им. В.И. Ульянова при поддержке Санкт-Петербургского политехнического университета Петра Великого. «Дискретные и цифровые фильтры» — второй курс специализации, посвященной цифровой обработке сигналов. В предыдущем курсе мы рассмотрели лишь самые простые вещи, связанные с концепцией дискретного времени — свойства дискретных сигналов и линейных стационарных дискретных систем. Но чтобы использовать такие системы для решения практических задач, нужно уметь их рассчитывать, добиваясь при этом желаемых свойств и характеристик. Кроме того, реальная система цифровой обработки сигналов — это вычислительное устройство, операции над числами в котором невозможны без появления некоторых погрешностей. При разработке и использовании таких систем наличие этих погрешностей нужно прогнозировать и учитывать. Об этих вопросах и пойдет речь во втором курсе цикла. Он объединяет несколько тем, посвященных разным аспектам расчета и построения систем, реализующих фильтрацию сигнала, а также вычислительным погрешностям, возникающим в цифровых системах. Знания, полученные в этом курсе, позволят вам двигаться дальше — к пониманию еще более сложных методов и алгоритмов. Цель курса: Сформировать у слушателей представление о сущности и применении дискретного преобразования Фурье, о методах расчета дискретных фильтров с заданными свойствами, о способах изменения частоты дискретизации сигнала, о проявлениях эффектов квантования и округления в системах цифровой обработки сигналов. В результате обучения слушатели будут: * Знать определение и свойства дискретного преобразования Фурье. * Понимать принципы расчета дискретных фильтров с заданными свойствами. * Уметь выполнять расчеты, связанные с анализом вычислительных погрешностей в системах цифровой обработки сигналов.
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This course is highly relevant to those in computer science, electrical engineering, and telecommunications seeking to expand their knowledge of digital signal processing
Teaches discrete Fourier transform and its properties, providing foundational knowledge for further study
Equips learners with methods to calculate discrete filters, empowering them to design systems that meet specific requirements
Addresses computational errors in digital systems, ensuring learners can anticipate and mitigate these issues in their own projects
Provides a clear and structured curriculum, guiding learners through complex concepts in a logical manner

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Reviews summary

Second course in digital signal processing: filters

An in-depth look into filter calculation and construction. Concepts are explained well but some topics may need further explanation in the lectures.
Teaches filter calculation and construction methods.
Requires a background in math.
" Серьезный курс. Требует уверенного знания математики в объеме двух курсов инженерных специальностей. "
Some concepts may need further explanation.
"Часто бывает такое, что в лекциях недостаточно разобрана тема, после чего она даётся на оценочном тесте."

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Career center

Learners who complete Цифровая обработка сигналов Часть 2. Дискретные и цифровые фильтры will develop knowledge and skills that may be useful to these careers:
Signal Processing Engineer
A Signal Processing Engineer designs and implements systems for processing signals, which can be used in various applications such as telecommunications, audio/video processing, and medical imaging. With the knowledge of discrete Fourier transform, filter design techniques, and computational errors gained from the course, you can effectively develop and optimize signal processing systems.
Telecommunications Engineer
A Telecommunications Engineer designs, develops, and maintains telecommunications systems, such as mobile networks, fiber optic networks, and satellite systems. The course provides valuable knowledge in digital signal processing techniques, including filter design and computational errors, which are essential for optimizing signal transmission and reception in telecommunications systems.
Audio Engineer
An Audio Engineer is responsible for recording, mixing, and mastering audio for various purposes, such as music production, film, and broadcasting. The course provides a solid foundation in understanding digital audio processing techniques, including filter design and computational errors, which are crucial for optimizing audio quality and achieving desired sound effects.
Medical Imaging Scientist
A Medical Imaging Scientist develops and applies imaging techniques for medical diagnosis and treatment. The course provides a solid foundation in digital signal processing techniques, including filter design and computational errors, which are critical for optimizing image quality and accuracy in medical imaging applications.
Control Systems Engineer
A Control Systems Engineer designs and implements systems to control various processes, such as industrial automation, robotics, and aerospace systems. The course provides a strong foundation in understanding the principles of digital control systems, including filter design and computational errors, which are critical for designing stable and high-performance control systems.
Data Scientist
A Data Scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. The course, by covering topics such as discrete Fourier transform, filter design techniques, and computational errors, provides a solid foundation for understanding and applying data science concepts in real-world applications.
Data Analyst
A Data Analyst makes use of data to extract insights that can help businesses make informed decisions. With the concepts of discrete time properties and linear stationary discrete systems, you can build a strong foundation in understanding how to analyze data and draw meaningful conclusions. The course also delves into issues of computational errors, which is a common challenge faced by Data Analysts when working with real-world data.
Biomedical Engineer
A Biomedical Engineer designs and develops medical devices and systems, such as pacemakers, MRI machines, and prosthetics. The course's coverage of discrete Fourier transform, filter design techniques, and computational errors provides valuable knowledge for understanding and optimizing the signal processing aspects of biomedical devices and systems.
Geophysicist
A Geophysicist studies the physical properties of the Earth and its surroundings using various techniques, such as seismic imaging and electromagnetic surveys. The course provides a solid foundation in digital signal processing techniques, including filter design and computational errors, which are essential for analyzing and interpreting geophysical data.
Embedded Systems Engineer
An Embedded Systems Engineer designs, develops, and maintains embedded systems, which are computer systems embedded within larger mechanical or electrical systems. The course's coverage of discrete Fourier transform, filter design techniques, and computational errors provides valuable knowledge for designing and implementing efficient and reliable embedded systems.
Computer Vision Engineer
A Computer Vision Engineer develops and implements systems that enable computers to interpret and understand visual data, such as images and videos. The course may provide valuable knowledge in digital signal processing techniques, including filter design and computational errors, which can be applied to optimize image and video processing algorithms.
Robotics Engineer
A Robotics Engineer designs, develops, and maintains robots for various applications, such as industrial automation, healthcare, and space exploration. The course may provide useful knowledge in digital signal processing techniques, including filter design and computational errors, which can be applied to optimize sensor data processing and control algorithms in robotics systems.
Electrical Engineer
An Electrical Engineer designs, develops, and maintains electrical systems, such as power generation and distribution systems, electronic circuits, and telecommunications networks. The course may provide useful knowledge in digital signal processing techniques, including filter design and computational errors, which can be applied to optimize signal processing algorithms in electrical systems.
Financial Analyst
A Financial Analyst analyzes financial data and provides recommendations for investment decisions. The course may provide useful insights into the application of digital signal processing techniques, including filter design and computational errors, in analyzing financial markets and making informed investment decisions.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. The course may provide useful insights into the application of digital signal processing techniques, including filter design and computational errors, in developing software for various industries, such as telecommunications, healthcare, and finance.

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