Digital Audio Signal Processing

Digital Audio Signal Processing PDF

Author: Udo Zölzer

Publisher: John Wiley & Sons

Published: 2022-02-24

Total Pages: 420

ISBN-13: 1119832691

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Digital Audio Signal Processing The fully revised new edition of the popular textbook, featuring additional MATLAB exercises and new algorithms for processing digital audio signals Digital Audio Signal Processing (DASP) techniques are used in a variety of applications, ranging from audio streaming and computer-generated music to real-time signal processing and virtual sound processing. Digital Audio Signal Processing provides clear and accessible coverage of the fundamental principles and practical applications of digital audio processing and coding. Throughout the book, the authors explain a wide range of basic audio processing techniques and highlight new directions for automatic tuning of different algorithms and discuss state- of-the-art DASP approaches. Now in its third edition, this popular guide is fully updated with the latest signal processing algorithms for audio processing. Entirely new chapters cover nonlinear processing, Machine Learning (ML) for audio applications, distortion, soft/hard clipping, overdrive, equalizers and delay effects, sampling and reconstruction, and more. Covers the fundamentals of quantization, filters, dynamic range control, room simulation, sampling rate conversion, and audio coding Describes DASP techniques, their theoretical foundations, and their practical applications Discusses modern studio technology, digital transmission systems, storage media, and home entertainment audio components Features a new introductory chapter and extensively revised content throughout Provides updated application examples and computer-based activities supported with MATLAB exercises and interactive JavaScript applets via an author-hosted companion website Balancing essential concepts and technological topics, Digital Audio Signal Processing, Third Edition remains the ideal textbook for advanced music technology and engineering students in audio signal processing courses. It is also an invaluable reference for audio engineers, hardware and software developers, and researchers in both academia and industry.

Signal, Audio and Image Processing

Signal, Audio and Image Processing PDF

Author: Dr. Hidaia Mahmood Alassouli

Publisher: Dr. Hidaia Mahmood Alassouli

Published: 2020-04-02

Total Pages: 73

ISBN-13:

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This project shows some selected signal techniques, including image and audio processing, using the Matlab digital signal processing and image processing toolboxes. The project is divided to 3 parts. Part I includes design and implementation of different types of filters for filtering signal that has different sinusoidal frequency components or noise. The comparison was made between FIR low pass flter, butterworth filter, Chebycheve Type I low pass filter and Chebycheve Type II low pass filter. Then different types of IIR Butterworth filters were designed and implemented to filter a signal that has many harmonics components, including low pass filter, high pass filter, stop band filter and band pass filter. Part II examined audio filtering in the sense of specific frequency suppression and extraction. There are many different types of filters available for the construction of filters. We will specifically use the Butterworth filter. An audio signal was read and different types of filters, including low pass filter, high pass filter, stop band filter and band pass filter, were designed and implemented in order to filter the audio signal from some frequency bands. Then the discrete cosine transform compression examined on the audio signal at different compression rates: 50%, 75% , 87.5% Part III deals with image processing; the project shows examples in smoothing, sharpening, and edge detection. Other useful operations on the image were tested, including image cropping, image resizing, image, histogram equalization and altering image brightness

Signal, Audio and Image Processing

Signal, Audio and Image Processing PDF

Author: Dr. Hidaia Mahmood Alassouli

Publisher: Lulu.com

Published: 2021-03-23

Total Pages: 72

ISBN-13: 1387887815

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This project shows some selected signal techniques, including image and audio processing, using the Matlab digital signal processing and image processing toolboxes. The project is divided to 3 parts. Part I includes design and implementation of different types of filters for filtering signal that has different sinusoidal frequency components or noise. The comparison was made between FIR low pass flter, butterworth filter, Chebycheve Type I low pass filter and Chebycheve Type II low pass filter. Then different types of IIR Butterworth filters were designed and implemented to filter a signal that has many harmonics components, including low pass filter, high pass filter, stop band filter and band pass filter. Part II examined audio filtering in the sense of specific frequency suppression and extraction. There are many different types of filters available for the construction of filters. We will specifically use the Butterworth filter. An audio signal was read and different types of filters, including low pass filter, high pass filter, stop band filter and band pass filter, were designed and implemented in order to filter the audio signal from some frequency bands. Then the discrete cosine transform compression examined on the audio signal at different compression rates: 50%, 75%, 87.5% Part III deals with image processing; the project shows examples in smoothing, sharpening, and edge detection. Other useful operations on the image were tested, including image cropping, image resizing, image, histogram equalization and altering image brightness

Audio Signal Processing and Coding

Audio Signal Processing and Coding PDF

Author: Andreas Spanias

Publisher: John Wiley & Sons

Published: 2006-09-11

Total Pages: 544

ISBN-13: 047004196X

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An in-depth treatment of algorithms and standards for perceptual coding of high-fidelity audio, this self-contained reference surveys and addresses all aspects of the field. Coverage includes signal processing and perceptual (psychoacoustic) fundamentals, details on relevant research and signal models, details on standardization and applications, and details on performance measures and perceptual measurement systems. It includes a comprehensive bibliography with over 600 references, computer exercises, and MATLAB-based projects for use in EE multimedia, computer science, and DSP courses. An ftp site containing supplementary material such as wave files, MATLAB programs and workspaces for the students to solve some of the numerical problems and computer exercises in the book can be found at ftp://ftp.wiley.com/public/sci_tech_med/audio_signal

IPython Interactive Computing and Visualization Cookbook

IPython Interactive Computing and Visualization Cookbook PDF

Author: Cyrille Rossant

Publisher: Packt Publishing Ltd

Published: 2014-09-25

Total Pages: 899

ISBN-13: 178328482X

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Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists... Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.

Some Case Studies on Signal, Audio and Image Processing Using Matlab

Some Case Studies on Signal, Audio and Image Processing Using Matlab PDF

Author: Dr. Hedaya Mahmood Alasooly

Publisher: BookRix

Published: 2020-05-30

Total Pages: 89

ISBN-13: 3748743807

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This project shows some selected signal techniques, including image and audio processing, using the Matlab digital signal processing and image processing toolboxes. The project is divided to 3 parts. Part I includes design and implementation of different types of filters for filtering signal that has different sinusoidal frequency components or noise. The comparison was made between FIR low pass flter, butterworth filter, Chebycheve Type I low pass filter and Chebycheve Type II low pass filter. Then different types of IIR Butterworth filters were designed and implemented to filter a signal that has many harmonics components, including low pass filter, high pass filter, stop band filter and band pass filter. Part II examined audio filtering in the sense of specific frequency suppression and extraction. There are many different types of filters available for the construction of filters. We will specifically use the Butterworth filter. An audio signal was read and different types of filters, including low pass filter, high pass filter, stop band filter and band pass filter, were designed and implemented in order to filter the audio signal from some frequency bands. Then the discrete cosine transform compression examined on the audio signal at different compression rates: 50%, 75% , 87.5% Part III deals with image processing; the project shows examples in smoothing, sharpening, and edge detection. Other useful operations on the image were tested, including image cropping, image resizing, image, histogram equalization and altering image brightness

Strengthening Deep Neural Networks

Strengthening Deep Neural Networks PDF

Author: Katy Warr

Publisher: "O'Reilly Media, Inc."

Published: 2019-07-03

Total Pages: 246

ISBN-13: 1492044903

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As deep neural networks (DNNs) become increasingly common in real-world applications, the potential to deliberately "fool" them with data that wouldn’t trick a human presents a new attack vector. This practical book examines real-world scenarios where DNNs—the algorithms intrinsic to much of AI—are used daily to process image, audio, and video data. Author Katy Warr considers attack motivations, the risks posed by this adversarial input, and methods for increasing AI robustness to these attacks. If you’re a data scientist developing DNN algorithms, a security architect interested in how to make AI systems more resilient to attack, or someone fascinated by the differences between artificial and biological perception, this book is for you. Delve into DNNs and discover how they could be tricked by adversarial input Investigate methods used to generate adversarial input capable of fooling DNNs Explore real-world scenarios and model the adversarial threat Evaluate neural network robustness; learn methods to increase resilience of AI systems to adversarial data Examine some ways in which AI might become better at mimicking human perception in years to come

Applications of Digital Signal Processing to Audio and Acoustics

Applications of Digital Signal Processing to Audio and Acoustics PDF

Author: Mark Kahrs

Publisher: Springer Science & Business Media

Published: 2005-12-11

Total Pages: 569

ISBN-13: 030647042X

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Karlheinz Brandenburg and Mark Kahrs With the advent of multimedia, digital signal processing (DSP) of sound has emerged from the shadow of bandwidth limited speech processing. Today, the main appli cations of audio DSP are high quality audio coding and the digital generation and manipulation of music signals. They share common research topics including percep tual measurement techniques and analysis/synthesis methods. Smaller but nonetheless very important topics are hearing aids using signal processing technology and hardware architectures for digital signal processing of audio. In all these areas the last decade has seen a significant amount of application oriented research. The topics covered here coincide with the topics covered in the biannual work shop on “Applications of Signal Processing to Audio and Acoustics”. This event is sponsored by the IEEE Signal Processing Society (Technical Committee on Audio and Electroacoustics) and takes place at Mohonk Mountain House in New Paltz, New York. A short overview of each chapter will illustrate the wide variety of technical material presented in the chapters of this book. John Beerends: Perceptual Measurement Techniques. The advent of perceptual measurement techniques is a byproduct of the advent of digital coding for both speech and high quality audio signals. Traditional measurement schemes are bad estimates for the subjective quality after digital coding/decoding. Listening tests are subject to sta tistical uncertainties and the basic question of repeatability in a different environment.

Fundamentals of Image, Audio, and Video Processing Using MATLAB®

Fundamentals of Image, Audio, and Video Processing Using MATLAB® PDF

Author: Ranjan Parekh

Publisher: CRC Press

Published: 2021-04-15

Total Pages: 407

ISBN-13: 1000374149

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Fundamentals of Image, Audio, and Video Processing Using MATLAB® introduces the concepts and principles of media processing and its applications in pattern recognition by adopting a hands-on approach using program implementations. The book covers the tools and techniques for reading, modifying, and writing image, audio, and video files using the data analysis and visualization tool MATLAB®. Key Features: Covers fundamental concepts of image, audio, and video processing Demonstrates the use of MATLAB® on solving problems on media processing Discusses important features of Image Processing Toolbox, Audio System Toolbox, and Computer Vision Toolbox MATLAB® codes are provided as answers to specific problems Illustrates the use of Simulink for audio and video processing Handles processing techniques in both the Spatio-Temporal domain and Frequency domain This is a perfect companion for graduate and post-graduate students studying courses on image processing, speech and language processing, signal processing, video object detection and tracking, and related multimedia technologies, with a focus on practical implementations using programming constructs and skill developments. It will also appeal to researchers in the field of pattern recognition, computer vision and content-based retrieval, and for students of MATLAB® courses dealing with media processing, statistical analysis, and data visualization. Dr. Ranjan Parekh, PhD (Engineering), is Professor at the School of Education Technology, Jadavpur University, Calcutta, India, and is involved with teaching subjects related to Graphics and Multimedia at the post-graduate level. His research interest includes multimedia information processing, pattern recognition, and computer vision.