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Author: Todd Moon
Publisher: McGraw-Hill Education
ISBN: 9781260458930
Category : Technology & Engineering
Languages : en
Pages : 384
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Book Description
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. A no-nonsense guide to the fundamentals and applications of statistical signal processing Ideal for upper-undergraduate and graduate courses, this engineering textbook offers key signal analysis principles and uses and explains the necessary underlying mathematics. Coverage includes representation and approximation theory in vector spaces, the orthogonality principle, the least squares problem, minimum mean square estimation, and the Wiener-Hopf equation. Signal Analysis: A Concise Guide clearly explains linear systems and signals and the concepts behind them. The book covers matrix factorizations, optimal linear filter theory, classical and modern spectral estimation, adaptive filters, and processing of spatial arrays. You will also explore linear optima filters, eigrn decomposition methods, the singular value decomposition, adaptive linear filters, noise cancellation, and spectral estimation. • Includes exercises for computer implementation using MATLAB • Presents the core material in a succinct format • Written by a team of renowned academics with multiple teaching awards
Author: Todd Moon
Publisher: McGraw-Hill Education
ISBN: 9781260458930
Category : Technology & Engineering
Languages : en
Pages : 384
Get Book Here
Book Description
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. A no-nonsense guide to the fundamentals and applications of statistical signal processing Ideal for upper-undergraduate and graduate courses, this engineering textbook offers key signal analysis principles and uses and explains the necessary underlying mathematics. Coverage includes representation and approximation theory in vector spaces, the orthogonality principle, the least squares problem, minimum mean square estimation, and the Wiener-Hopf equation. Signal Analysis: A Concise Guide clearly explains linear systems and signals and the concepts behind them. The book covers matrix factorizations, optimal linear filter theory, classical and modern spectral estimation, adaptive filters, and processing of spatial arrays. You will also explore linear optima filters, eigrn decomposition methods, the singular value decomposition, adaptive linear filters, noise cancellation, and spectral estimation. • Includes exercises for computer implementation using MATLAB • Presents the core material in a succinct format • Written by a team of renowned academics with multiple teaching awards
Author: Amir-Homayoon Najmi
Publisher: McGraw Hill Professional
ISBN: 1260458946
Category : Technology & Engineering
Languages : en
Pages : 353
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Book Description
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. A comprehensive introduction to the mathematical principles and algorithms in statistical signal processing and modern neural networks. This text is an expanded version of a graduate course on advanced signal processing at the Johns Hopkins University Whiting school program for professionals with students from electrical engineering, physics, computer and data science, and mathematics backgrounds. It covers the theory underlying applications in statistical signal processing including spectral estimation, linear prediction, adaptive filters, and optimal processing of uniform spatial arrays. Unique among books on the subject, it also includes a comprehensive introduction to modern neural networks with examples in time series and image classification. Coverage includes: Mathematical structures of signal spaces and matrix factorizations linear time-invariant systems and transforms Least squares filters Random variables, estimation theory, and random processes Spectral estimation and autoregressive signal models linear prediction and adaptive filters Optimal processing of linear arrays Neural networks
Author: Amir-Homayoon Najmi
Publisher: JHU Press
ISBN: 1421404966
Category : Mathematics
Languages : en
Pages : 303
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Book Description
Introduced nearly three decades ago as a variable resolution alternative to the Fourier transform, a wavelet is a short oscillatory waveform for analysis of transients. The discrete wavelet transform has remarkable multi-resolution and energy-compaction properties. Amir-Homayoon Najmi’s introduction to wavelet theory explains this mathematical concept clearly and succinctly. Wavelets are used in processing digital signals and imagery from myriad sources. They form the backbone of the JPEG2000 compression standard, and the Federal Bureau of Investigation uses biorthogonal wavelets to compress and store its vast database of fingerprints. Najmi provides the mathematics that demonstrate how wavelets work, describes how to construct them, and discusses their importance as a tool to investigate and process signals and imagery. He reviews key concepts such as frames, localizing transforms, orthogonal and biorthogonal bases, and multi-resolution. His examples include the Haar, the Shannon, and the Daubechies families of orthogonal and biorthogonal wavelets. Our capacity and need for collecting and transmitting digital data is increasing at an astonishing rate. So too is the importance of wavelets to anyone working with and analyzing digital data. Najmi’s primer will be an indispensable resource for those in computer science, the physical sciences, applied mathematics, and engineering who wish to obtain an in-depth understanding and working knowledge of this fascinating and evolving field.
Author: Danilo Mandic
Publisher: Springer Science & Business Media
ISBN: 0387743677
Category : Technology & Engineering
Languages : en
Pages : 335
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Book Description
This book brings together the latest research achievements from signal processing and related disciplines, consolidating existing and proposed directions in DSP-based knowledge extraction and information fusion. The book includes contributions presenting both novel algorithms and existing applications, emphasizing on-line processing of real-world data. Readers discover applications that solve biomedical, industrial, and environmental problems.
Author: Richard G. Lyons
Publisher: Pearson Education
ISBN: 0133804429
Category : Business & Economics
Languages : en
Pages : 206
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Book Description
Using everyday examples and simple diagrams, two leading DSP consultants and instructors completely demystify signal processing with this text. Students will discover what digital signals are, how they're generated, and how they're changing life. Students will learn all they need to know about digital signal collection, filtering, analysis, and more, and how DSP works in today's most exciting devices and applications.
Author: Michael M. Richter
Publisher: Springer
ISBN: 9783319453712
Category : Computers
Languages : en
Pages : 0
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Book Description
Signal processing captures, interprets, describes and manipulates physical phenomena. Mathematics, statistics, probability, and stochastic processes are among the signal processing languages we use to interpret real-world phenomena, model them, and extract useful information. This book presents different kinds of signals humans use and applies them for human machine interaction to communicate. Signal Processing and Machine Learning with Applications presents methods that are used to perform various Machine Learning and Artificial Intelligence tasks in conjunction with their applications. It is organized in three parts: Realms of Signal Processing; Machine Learning and Recognition; and Advanced Applications and Artificial Intelligence. The comprehensive coverage is accompanied by numerous examples, questions with solutions, with historical notes. The book is intended for advanced undergraduate and postgraduate students, researchers and practitioners who are engaged with signal processing, machine learning and the applications.
Author: Andreas Spanias
Publisher: John Wiley & Sons
ISBN: 047004196X
Category : Technology & Engineering
Languages : en
Pages : 544
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Book Description
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
Author: T. Chonavel
Publisher: Springer Science & Business Media
ISBN: 1447101391
Category : Technology & Engineering
Languages : en
Pages : 334
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Book Description
The only book on the subject at this level, this is a well written formalised and concise presentation of the basis of statistical signal processing. It teaches a wide variety of techniques, demonstrating how they can be applied to many different situations.
Author: Theodoros Giannakopoulos
Publisher: Academic Press
ISBN: 0080993893
Category : Computers
Languages : en
Pages : 283
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Book Description
Introduction to Audio Analysis serves as a standalone introduction to audio analysis, providing theoretical background to many state-of-the-art techniques. It covers the essential theory necessary to develop audio engineering applications, but also uses programming techniques, notably MATLAB®, to take a more applied approach to the topic. Basic theory and reproducible experiments are combined to demonstrate theoretical concepts from a practical point of view and provide a solid foundation in the field of audio analysis. Audio feature extraction, audio classification, audio segmentation, and music information retrieval are all addressed in detail, along with material on basic audio processing and frequency domain representations and filtering. Throughout the text, reproducible MATLAB® examples are accompanied by theoretical descriptions, illustrating how concepts and equations can be applied to the development of audio analysis systems and components. A blend of reproducible MATLAB® code and essential theory provides enable the reader to delve into the world of audio signals and develop real-world audio applications in various domains. - Practical approach to signal processing: The first book to focus on audio analysis from a signal processing perspective, demonstrating practical implementation alongside theoretical concepts - Bridge the gap between theory and practice: The authors demonstrate how to apply equations to real-life code examples and resources, giving you the technical skills to develop real-world applications - Library of MATLAB code: The book is accompanied by a well-documented library of MATLAB functions and reproducible experiments
Author: Paul Hill
Publisher: CRC Press
ISBN: 0429813961
Category : Computers
Languages : en
Pages : 354
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Book Description
Speech and audio processing has undergone a revolution in preceding decades that has accelerated in the last few years generating game-changing technologies such as truly successful speech recognition systems; a goal that had remained out of reach until very recently. This book gives the reader a comprehensive overview of such contemporary speech and audio processing techniques with an emphasis on practical implementations and illustrations using MATLAB code. Core concepts are firstly covered giving an introduction to the physics of audio and vibration together with their representations using complex numbers, Z transforms and frequency analysis transforms such as the FFT. Later chapters give a description of the human auditory system and the fundamentals of psychoacoustics. Insights, results, and analyses given in these chapters are subsequently used as the basis of understanding of the middle section of the book covering: wideband audio compression (MP3 audio etc.), speech recognition and speech coding. The final chapter covers musical synthesis and applications describing methods such as (and giving MATLAB examples of) AM, FM and ring modulation techniques. This chapter gives a final example of the use of time-frequency modification to implement a so-called phase vocoder for time stretching (in MATLAB). Features A comprehensive overview of contemporary speech and audio processing techniques from perceptual and physical acoustic models to a thorough background in relevant digital signal processing techniques together with an exploration of speech and audio applications. A carefully paced progression of complexity of the described methods; building, in many cases, from first principles. Speech and wideband audio coding together with a description of associated standardised codecs (e.g. MP3, AAC and GSM). Speech recognition: Feature extraction (e.g. MFCC features), Hidden Markov Models (HMMs) and deep learning techniques such as Long Short-Time Memory (LSTM) methods. Book and computer-based problems at the end of each chapter. Contains numerous real-world examples backed up by many MATLAB functions and code.
