Digital Signal Processing System Design: LabVIEW-Based Hybrid Programming
by Nasser Kehtarnavaz University of Texas at Dallas With laboratory contributions by Namjin Kim and Qingzhong Peng
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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.
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.”...
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.
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).
Real Time Digital Signal Processing Adaptive filters are time varying, filter characteristics such as bandwidth and frequency response change with time. Thus the filter coefficients cannot be determined when the filter is implemented. The coefficients of the adaptive filter are adjusted automatically by an adaptive algorithm based on incoming signals. This has the important effect of enabling adaptive filters
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.
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
(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.
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.
A significant revision of a best-selling text for the introductory digital signal processing course. This book presents the fundamentals of discrete-time signals, systems, and modern digital processing and applications for students in electrical engineering, computer engineering, and computer science.The book is suitable for either a one-semester or a two-semester undergraduate level course in discrete systems and digital signal processing. It is also intended for use in a one-semester first-year graduate-level course in digital signal processing.
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....
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.
After studying this chapter you will be able to: Understand how to convert the analog to digital signal, have a thorough grasp of signal processing in linear time-invariant systems, understand the z-transform and Fourier transforms in analyzing the signal and systems, be able to design and implement FIR and IIR filters.
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).
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,...
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.
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.