Handbook of Signal Processing in Acoustics


Book Description

The Handbook of Signal Processing in Acoustics brings together a wide range of perspectives from over 100 authors to reveal the interdisciplinary nature of the subject. It brings the key issues from both acoustics and signal processing into perspective and is a unique resource for experts and practitioners alike to find new ideas and techniques within the diversity of signal processing in acoustics.




Adaptive Filtering


Book Description

In the fifth edition of this textbook, author Paulo S.R. Diniz presents updated text on the basic concepts of adaptive signal processing and adaptive filtering. He first introduces the main classes of adaptive filtering algorithms in a unified framework, using clear notations that facilitate actual implementation. Algorithms are described in tables, which are detailed enough to allow the reader to verify the covered concepts. Examples address up-to-date problems drawn from actual applications. Several chapters are expanded and a new chapter ‘Kalman Filtering’ is included. The book provides a concise background on adaptive filtering, including the family of LMS, affine projection, RLS, set-membership algorithms and Kalman filters, as well as nonlinear, sub-band, blind, IIR adaptive filtering, and more. Problems are included at the end of chapters. A MATLAB package is provided so the reader can solve new problems and test algorithms. The book also offers easy access to working algorithms for practicing engineers.




Deep Learning Approaches for Spoken and Natural Language Processing


Book Description

This book provides insights into how deep learning techniques impact language and speech processing applications. The authors discuss the promise, limits and the new challenges in deep learning. The book covers the major differences between the various applications of deep learning and the classical machine learning techniques. The main objective of the book is to present a comprehensive survey of the major applications and research oriented articles based on deep learning techniques that are focused on natural language and speech signal processing. The book is relevant to academicians, research scholars, industrial experts, scientists and post graduate students working in the field of speech signal and natural language processing and would like to add deep learning to enhance capabilities of their work. Discusses current research challenges and future perspective about how deep learning techniques can be applied to improve NLP and speech processing applications; Presents and escalates the research trends and future direction of language and speech processing; Includes theoretical research, experimental results, and applications of deep learning.




Learning Approaches in Signal Processing


Book Description

Coupled with machine learning, the use of signal processing techniques for big data analysis, Internet of things, smart cities, security, and bio-informatics applications has witnessed explosive growth. This has been made possible via fast algorithms on data, speech, image, and video processing with advanced GPU technology. This book presents an up-to-date tutorial and overview on learning technologies such as random forests, sparsity, and low-rank matrix estimation and cutting-edge visual/signal processing techniques, including face recognition, Kalman filtering, and multirate DSP. It discusses the applications that make use of deep learning, convolutional neural networks, random forests, etc. The applications include super-resolution imaging, fringe projection profilometry, human activities detection/capture, gesture recognition, spoken language processing, cooperative networks, bioinformatics, DNA, and healthcare.




Introduction to Engineering


Book Description

This lecture provides a hands-on glimpse of the field of electrical engineering. The introduced applications utilize the NI ELVIS hardware and software platform to explore concepts such as circuits, power, analog sensing, and introductory analog signal processing such as signal generation, analog filtering, and audio and music processing. These principals and technologies are introduced in a very practical way and are fundamental to many of the electronic devices we use today. Some examples include photodetection, analog signal (audio, light, temperature) level meter, and analog music equalizer. Table of Contents: Getting Familiar with NI ELVIS / Analog Signal Level Meter Using LEDs / Noise Removal Using Analog Filters / Music Equalizer Using Op-Amps: Volume and Treble Control / Music Composer Using 555 Timers