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.”...
Top-Selling DSP Book for Seven Straight Years-Now Fully Updated! Understanding Digital Signal Processing, Third Edition,is quite simply the best resource for engineers and other technical professionals who want to master and apply today's latest DSP techniques. Richard G. Lyons has updated and expanded his best-selling second edition to reflect the newest technologies, building on the exceptionally readable coverage that made it the favorite of DSP professionals worldwide.
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.
Signals represent information about data, voice, audio, image, video… There are many ways to
classify signals but here we categorize signals as either analog (continuous-time) or digital (discretetime).
Signal processing is to use circuits and systems (hardware and software) to act on input signal
to give output signal which differs from the input, the way we would like to.
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).
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.
Digital filters, together with signal processing, are being employed in the new technologies and information systems, and are implemented in different areas and applications. Digital filters and signal processing are used with no costs and they can be adapted to different cases with great flexibility and reliability. This book presents advanced developments in digital filters and signal process methods covering different cases studies.
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.
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....
Recent advances in genomic studies have stimulated synergetic research and development in many cross-disciplinary areas. Genomic data, especially the recent large-scale microarray gene expression data, represents enormous challenges for signal processing and statistics in processing these vast data to reveal the complex biological functionality. This perspective naturally leads to a new field, genomic signal processing (GSP)
This volume describes the essential tools and techniques of statistical signal processing. At every stage, theoretical ideas are linked to specific applications in communications and signal processing. The book begins with an overview of basic probability, random objects, expectation, and second-order moment theory, followed by a wide variety of examples of the most popular random process models and their basic uses and properties.
Ebook Signal Processing and Lindear Systems presents a comprehensive treatment of signals and linear systems suitable for juniors and seniors in electrical engineering. The book contains most of the material from author earlier popular book Linear Systems and Signals (1992) with added chapters on analog.
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.