Digital signal processing

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  • Suitable for a one- or two-semester undergraduate-level electrical engineering, computer engineering, and computer science course in Discrete Systems and Digital Signal Processing. Assumes some prior knowledge of advanced calculus, linear systems for continuous-time signals, and Fourier series and transforms. Giving students a sound balance of theory and practical application, this no-nonsense text presents the fundamental concepts and techniques of modern digital signal processing with related algorithms and applications.

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  • For many years, I have been teaching DSP (Digital Signal Processing) lab courses using various TI (Texas Instruments) DSP platforms. One question I have been getting from students in a consistent way is, “Do we have to know C to take DSP lab courses?” Until last year, my response was, “Yes, C is a prerequisite for taking DSP lab courses.” However, last year for the first time, I provided a different response by saying, “Though preferred, it is not required to know C to take DSP lab courses.”...

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  • With its active, hands-on learning approach, this text enables readers to master the underlying principles of digital signal processing and its many applications in industries such as digital television, mobile and broadband communications, and medical/scientific devices. Carefully developed MATLAB® examples throughout the text illustrate the mathematical concepts and use of digital signal processing algorithms.

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  • This book is a tutorial on digital techniques for waveform generation, digital filters, and digital signal processing tools and techniques. The typical chapter begins with some theoretical material followed by working examples and experiments using the TMS320C6713-based DSPStarter Kit (DSK). The C6713 DSK is TI's newest signal processor based on the C6x processor (replacing the C6711 DSK).

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  • The main thrust is to provide students with a solid understanding of a number of important and related advanced topics in digital signal processing such as Wiener filters, power spectrum estimation, signal modeling and adaptive filtering. Scores of worked examples illustrate fine points, compare techniques and algorithms and facilitate comprehension of fundamental concepts. Also features an abundance of interesting and challenging problems at the end of every chapter.

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  • (NB) Phần 1 Giáo trình Xử lý số tín hiệu (Digital signal processing) do Đoàn Thị Thu Thủy, Phạm Hữu Lộc biên soạn gồm nội dung 5 chương đầu tài liệu. Nội dung phần này trình bày đại cương về tín hiệu và nhiễu, phân tích Fourier, lấy mẫu và khôi phục tín hiệu, tín hiệu và hệ thống rời rạc thời gian, phân tích trong miền thời gian và miền tần số.

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  • (NB) Phần 2 Giáo trình Xử lý số tín hiệu (Digital signal processing) gồm nội dung chương 6, chương 7. Nội dung phần này trình bày về biến đổi Z, hàm chuyển và ứng dụng.

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  • Digital Signal Processing (DSP) is formally defined as a digital operation performed on an input sequence of numbers (including feedback from the result of the digital operation). The sequence of numbers can represent anything from digitised human speech to stock price data, processed to detect hidden periodicities or pattern

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  • It is a great honor and pleasure for me to introduce this book “Applications of Digital Signal Processing” being published by InTech. The field of digital signal processing is at the heart of communications, biomedicine, defense applications, and so on. The field has experienced an explosive growth from its origins, with huge advances both in fundamental research and applications.

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  • Digital signal processing (DSP) covers a wide range of applications in which the implementation of high-performance systems to meet stringent requirements and performance constraints is receiving increasing attention both in the industrial and academic contexts. Conceived to be available to a wide audience, the aim of this book is to provide students, researchers, engineers and the industrial community with a guide to the latest advances in emerging issues in the design and implementation of DSP systems for application-specific circuits and programmable devices....

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  • Bài giảng Xử lý số tín hiệu (Digital signal processing) - Chương 7: Thiết kế bộ lọc số. Nội dung chính trong chương này cung cấp cho người học các kiến thức: Các bước thực hiện bộ lọc số, các yêu cầu của bộ lọc, thiết kế bộ lọc FIR dùng phương pháp cửa sổ, thiết kế bộ lọc IIR từ các bộ lọc thời gian liên tục,... Mời các bạn cùng tham khảo nội dung chi tiết.

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  • Bài giảng Xử lý số tín hiệu DPS (Digital Signal Processing): Chương 1 cung cấp cho người học những kiến thức: Xử lý số tín hiệu, khái niệm, lấy mẫu, phổ của tín hiệu lấy mẫu, khôi phục tín hiệu lấy mẫu, định lý lấy mẫu, các bộ tiền lọc chống chồng phổ,... Mời các bạn cùng tham khảo.

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  • There are many contents in this document: Digital Signal Processing Research Program, dvanced Telecommunications and Signal Processing Program, Combined Source and Channel Coding for High Definition Televisio.

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  • The paper presents a general overview of ultrasound signal processing and its digital implementation with emphasis on hardware-software partitioning. The available state of the art methods and systems of digital signal processing using both hardware and software are presented as well as the issues pertaining to algorithm implementation methodology.

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  • Lecture Digital signal processing - Chapter 4: FIR filtering and convolution includes content: Block processing methods (Convolution: direct form, convolution table; convolution: LTI form, LTI table; matrix form; flip-and-slide form; overlap-add block convolution method), sample processing methods.

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  • Lecture Digital signal processing - Chapter 6 introduce transfer function and digital filter realization. In this chapter, you will learn to: Transfer functions (Impulse response, difference equation, impulse response,...), digital filter realization (Direct form, canonical form, cascade form).

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  • Lecture Digital signal processing - Lecture 1 introduction, discrete-time signals and systems. After completing this chapter, students will be able: To make the students able to apply digital filters according to known filter specifications, to provide the knowledge about the principles behind the discrete Fourier transform (DFT) and its fast computation,...

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  • Lecture Digital signal processing - Lecture 4 present sampling and reconstruction. The main contents of this chapter include all of the following: Periodic sampling, „frequency domain representation, reconstruction, changing the sampling rate using discretetime processing.

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  • Lecture Digital signal processing - Lecture 7 presents the following content: Filter design, IIR filter design, analog filter design, IIR filter design by impulse invariance, IIR filter design by bilinear transformation.

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  • Lecture Digital signal processing - Lecture 4 introduce the discrete fourier transform. This lesson presents the following content: The discrete Fourier series, the Fourier transform of periodic signals, sampling the Fourier transform, the discrete Fourier transform, properties of the DFT, linear convolution using the DFT.

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