Signal Processing VI


Book Description

This was the sixth in the sequence of the international conferences promoted and organized by the European Association for Signal Processing. The conference has established itself as one of the world's largest and most important meetings on the subject. The 444 papers (in three volumes) are organized under 7 themes, containing the following topics:1. Theory of Signals and Systems:a) Detection, b) Estimation, c) Filtering, d)Spectral estimation, e) Adaptive systems, f) Modeling, g) Digital transforms, h) Digital filtering.2. Image Processing and Multidimensional Signal Processing:a) Coding, b) Enhancement, c) Restoration, d) Medical image processing.3. Speech Processing:a) Coding, b) Synthesis, c) Recognition and understanding, d) Enhancement.4. Implementations:a) Hardware, b) Software, c) VLSI, d) Novel Architectures, e) Array processing.5. Knowledge Engineering and Signal Processing:a) Expert systems, b) Pattern recognition, c) Signal interpretation, d) Image understanding.6. Neural Networks for Signal Processing:a) Theory, b) Speech, c) Vision, d) Implementations. 7. Applications:a) Radar, b) Sonar, c) Communications, d) Geophysics, e) Digital audio, f) Biomedics, g) Sensing, h) Robotics, i) Astrophysics, j) Mechanics, k) other. The diversity of topics in this 3-volume set, as well as the extraordinary tempo at which Signal Processing has progressed, attest to the permanent vitality of this area of research and development. Workers in signal processing will find in these papers the latest advances and results, as well as indications on future research and analysis in this rapidly developing field.




Think DSP


Book Description

If you understand basic mathematics and know how to program with Python, you’re ready to dive into signal processing. While most resources start with theory to teach this complex subject, this practical book introduces techniques by showing you how they’re applied in the real world. In the first chapter alone, you’ll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds. Author Allen Downey explains techniques such as spectral decomposition, filtering, convolution, and the Fast Fourier Transform. This book also provides exercises and code examples to help you understand the material. You’ll explore: Periodic signals and their spectrums Harmonic structure of simple waveforms Chirps and other sounds whose spectrum changes over time Noise signals and natural sources of noise The autocorrelation function for estimating pitch The discrete cosine transform (DCT) for compression The Fast Fourier Transform for spectral analysis Relating operations in time to filters in the frequency domain Linear time-invariant (LTI) system theory Amplitude modulation (AM) used in radio Other books in this series include Think Stats and Think Bayes, also by Allen Downey.




LabVIEW Digital Signal Processing


Book Description

LabVIEW Digital Signal Processing teaches engineers how to use the graphical programming language to create virtual instruments to handle to most sophisticated DSP applications. From basic filters to complex sampling mechanisms to signal generators, LabVIEW virtual instruments (VIs) can make DSP work faster and much less expensive – a particular boon to the many engineers working on cutting edge communications systems.




Digital Signal Processing


Book Description




VLSI Signal Processing, VI


Book Description







LabVIEW Signal Processing


Book Description

Get results fast, with LabVIEW Signal Processing! This practical guide to LabVIEW Signal Processing and control system capabilities is designed to help you get results fast. You'll understand LabVIEW's extensive analysis capabilities and learn to identify and use the best LabVIEW tool for each application. You'll review classical DSP and other essential topics, including control system theory, curve fitting, and linear algebra. Along the way, you'll use LabVIEW's tools to construct practical applications that illuminate: Arbitrary waveform generation. Aliasing, signal separation, and their effects. The separation of two signals close in frequency but differing in amplitudes. Predicting the cost of producing a product in multiple quantities. Noise removal in biomedical applications. Determination of system stability and design linear state feedback. The accompanying website contains the complete LabVIEW FDS evaluation version, including analysis library, relevant elements of the G Math Toolkit, and complete demos of several other important products, including the Digital Filter Design Toolkit and the Signal Processing Suite. Whether you're a professional or student, LabVIEW represents an extraordinary opportunity to streamline signal processing and control systems projects--and this book is all you need to get started.




Digital Signal Processing System-Level Design Using LabVIEW


Book Description

LabVIEW (Laboratory Virtual Instrumentation Engineering Workbench) developed by National Instruments is a graphical programming environment. Its ease of use allows engineers and students to streamline the creation of code visually, leaving time traditionally spent on debugging for true comprehension of DSP. This book is perfect for practicing engineers, as well as hardware and software technical managers who are familiar with DSP and are involved in system-level design. With this text, authors Kehtarnavaz and Kim have also provided a valuable resource for students in conventional engineering courses. The integrated lab exercises create an interactive experience which supports development of the hands-on skills essential for learning to navigate the LabVIEW program. Digital Signal Processing System-Level Design Using LabVIEW is a comprehensive tool that will greatly accelerate the DSP learning process. Its thorough examination of LabVIEW leaves no question unanswered. LabVIEW is the program that will demystify DSP and this is the book that will show you how to master it.* A graphical programming approach (LabVIEW) to DSP system-level design* DSP implementation of appropriate components of a LabVIEW designed system* Providing system-level, hands-on experiments for DSP lab or project courses




Digital Signal Processing System Design


Book Description

Digital Signal Processing System Design combines textual and graphical programming to form a hybrid programming approach, enabling a more effective means of building and analyzing DSP systems. The hybrid programming approach allows the use of previously developed textual programming solutions to be integrated into LabVIEW's highly interactive and visual environment, providing an easier and quicker method for building DSP systems. This book is an ideal introduction for engineers and students seeking to develop DSP systems in quick time. Features: - The only DSP laboratory book that combines textual and graphical programming - 12 lab experiments that incorporate C/MATLAB code blocks into the LabVIEW graphical programming environment via the MathScripting feature - Lab experiments covering basic DSP implementation topics including sampling, digital filtering, fixed-point data representation, frequency domain processing - Interesting applications using the hybrid programming approach, such as a software-defined radio system, a 4-QAM Modem, and a cochlear implant simulator - The only DSP project book that combines textual and graphical programming - 12 Lab projects that incorporate MATLAB code blocks into the LabVIEW graphical programming environment via the MathScripting feature - Interesting applications such as the design of a cochlear implant simulator and a software-defined radio system




EEG Signal Processing and Machine Learning


Book Description

EEG Signal Processing and Machine Learning Explore cutting edge techniques at the forefront of electroencephalogram research and artificial intelligence from leading voices in the field The newly revised Second Edition of EEG Signal Processing and Machine Learning delivers an inclusive and thorough exploration of new techniques and outcomes in electroencephalogram (EEG) research in the areas of analysis, processing, and decision making about a variety of brain states, abnormalities, and disorders using advanced signal processing and machine learning techniques. The book content is substantially increased upon that of the first edition and, while it retains what made the first edition so popular, is composed of more than 50% new material. The distinguished authors have included new material on tensors for EEG analysis and sensor fusion, as well as new chapters on mental fatigue, sleep, seizure, neurodevelopmental diseases, BCI, and psychiatric abnormalities. In addition to including a comprehensive chapter on machine learning, machine learning applications have been added to almost all the chapters. Moreover, multimodal brain screening, such as EEG-fMRI, and brain connectivity have been included as two new chapters in this new edition. Readers will also benefit from the inclusion of: A thorough introduction to EEGs, including neural activities, action potentials, EEG generation, brain rhythms, and EEG recording and measurement An exploration of brain waves, including their generation, recording, and instrumentation, abnormal EEG patterns and the effects of ageing and mental disorders A treatment of mathematical models for normal and abnormal EEGs Discussions of the fundamentals of EEG signal processing, including statistical properties, linear and nonlinear systems, frequency domain approaches, tensor factorization, diffusion adaptive filtering, deep neural networks, and complex-valued signal processing Perfect for biomedical engineers, neuroscientists, neurophysiologists, psychiatrists, engineers, students and researchers in the above areas, the Second Edition of EEG Signal Processing and Machine Learning will also earn a place in the libraries of undergraduate and postgraduate students studying Biomedical Engineering, Neuroscience and Epileptology.