Download or read book Multiscale Signal Analysis and Modeling written by Xiaoping Shen and published by Springer Science & Business Media. This book was released on 2012-09-18 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiscale Signal Analysis and Modeling presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory.
Download or read book Multiscale Signal Analysis and Modeling written by and published by Springer. This book was released on 2012-09-19 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Stochastic Modeling Approach to Multiscale Signal Processing written by Kenneth Chien-ko Chou and published by . This book was released on 1991 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Stochastic Modelling Approach to Multiscale Signal Processing written by Kenneth Chien-ko Chou and published by . This book was released on 1991 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multiscale Statistical Models for Signal and Image Processing written by and published by . This book was released on 2004 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are developing a general theory for multi scale signal and image modeling, processing, and analysis that matched to singularity-rich data, such as transients and images with edges. Using a linguistic analogy, our model can be interpreted as grammars that constrain the wavelet vocabulary. Our investigation focuses on probabilistic graph models (tree-based hidden Markov models) that can accurately, realistically, and efficiently represent singularity structure in the wavelet domain. Grammar design is being guided by a detailed study of the final structure of singularities using Besov spaces and multifractal analysis.
Download or read book Multiscale Analysis of Complex Time Series written by Jianbo Gao and published by John Wiley & Sons. This book was released on 2007-12-04 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: The only integrative approach to chaos and random fractal theory Chaos and random fractal theory are two of the most important theories developed for data analysis. Until now, there has been no single book that encompasses all of the basic concepts necessary for researchers to fully understand the ever-expanding literature and apply novel methods to effectively solve their signal processing problems. Multiscale Analysis of Complex Time Series fills this pressing need by presenting chaos and random fractal theory in a unified manner. Adopting a data-driven approach, the book covers: DNA sequence analysis EEG analysis Heart rate variability analysis Neural information processing Network traffic modeling Economic time series analysis And more Additionally, the book illustrates almost every concept presented through applications and a dedicated Web site is available with source codes written in various languages, including Java, Fortran, C, and MATLAB, together with some simulated and experimental data. The only modern treatment of signal processing with chaos and random fractals unified, this is an essential book for researchers and graduate students in electrical engineering, computer science, bioengineering, and many other fields.
Download or read book Higher Dimensional Signal Processing Via Multiscale Geometric Analysis written by and published by . This book was released on 2010 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: This project pursued a general theory for complex-valued multiscale signal and image modeling, processing, and analysis that is matched to singularity-rich data. Higher-dimensional signals that feature geometric manifold structures were of particular interest in developing theory and a practical toolset for analysis and processing. We pursued a three-pronged approach in creating new multiscale transforms, new geometric statistical models, and new manifold-based signal representations. The results of our research include (1) the Dual Tree Quaternion Wavelet, an efficient transform and analysis tool that features near shift invariance and linear computational complexity; (2) a geometric hidden Markov tree wavelet model, which accounts for geometric regularity by capturing the dependencies between complex wavelet coefficients along a contour; and (3) surflet representations of signal discontinuities with near optimal rate-distortion performance. These new tools have led to significant performance gains immediately applicable to a number of important Navy-relevant applications, including target detection and classification, image segmentation and fusion, and computer network traffic modeling.
Download or read book Multiscale Modeling of Cancer written by Vittorio Cristini and published by Cambridge University Press. This book was released on 2010-09-09 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical modeling, analysis and simulation are set to play crucial roles in explaining tumor behavior, and the uncontrolled growth of cancer cells over multiple time and spatial scales. This book, the first to integrate state-of-the-art numerical techniques with experimental data, provides an in-depth assessment of tumor cell modeling at multiple scales. The first part of the text presents a detailed biological background with an examination of single-phase and multi-phase continuum tumor modeling, discrete cell modeling, and hybrid continuum-discrete modeling. In the final two chapters, the authors guide the reader through problem-based illustrations and case studies of brain and breast cancer, to demonstrate the future potential of modeling in cancer research. This book has wide interdisciplinary appeal and is a valuable resource for mathematical biologists, biomedical engineers and clinical cancer research communities wishing to understand this emerging field.
Download or read book Multiscale Statistical Signal Processing written by Michèle Basseville and published by . This book was released on 1989 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multiscale Analysis Modeling and Processing of Higher Dimensional Geometric Data written by and published by . This book was released on 2007 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: The wavelet transform has emerged over the last decade as a powerful new tool for statistical signal processing. The wavelet domain provides a natural setting for many applications involving real-world signals and images, especially those rich in singularities (edges, ridges, and other transients). In this project, we extended wavelet transform modeling and processing algorithms to handle multidimensional signals that are smooth save for singularities along lower-dimensional manifolds. The key building block is a new quaternion wavelet transform (QWT) that generalizes the complex wavelet transform to higher dimensions using a multidimensional Hilbert transform. The QWT has a quaternion magnitude-phase representation that encodes image shifts in an absolute (x, y)-coordinate system and thus provides a theoretical framework for analyzing the phase behavior of 2-D image shifts. We conducted a thorough analysis of the QWT phase around edge regions and thereby developed efficient multiscale edge localization and flow/motion estimation algorithms for image registration based on the QWT phase.
Download or read book Wavelets and Multiscale Signal Processing written by Taylor & Francis Group and published by . This book was released on 2018-09-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Generative Signal Processing Through Multilayer Multiscale Wavelet Models written by Jieqian He and published by . This book was released on 2021 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wavelet analysis and deep learning are two popular fields for signal processing. The scattering transform from wavelet analysis is a recently proposed mathematical model for convolution neural networks. Signals with repeated patterns can be analyzed using the statistics from such models. Specifically, signals from certain classes can be recovered from related statistics. We first focus on recovering 1D deterministic dirac signals from multiscale statistics. We prove a dirac signal can be recovered from multiscale statistics up to a translation and reflection. Then we switch to a stochastic version, modeled using Poisson point processes, and prove wavelet statistics at small scales capture the intensity parameter of Poisson point processes. We also design a scattering generative adversarial network (GAN) to generate new Poisson point samples from statistics of multiple given samples. Next we consider texture images. We successfully synthesize new textures given one sample from the texture class through multiscale, multilayer wavelet models. Finally, we analyze and prove why the multiscale multilayer model is essential for signal recovery, especially natural texture images.
Download or read book Multiscale Statistical Modeling Approach to Monitoring Mechanical Systems written by Kenneth C. Chou and published by . This book was released on 1996 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal processing for condition based maintenance and equipment monitoring has focused in recent years on non-stationary signal analysis using time-frequency representations of the signal. These representations are used to identify non-stationary events in the signal that indicate some change in the state of a structure or a machine. It is important to be able to reliably detect such changes in real time to do necessary preventive maintenance and also to minimize unnecessary maintenance. While transformations such as the Wigner-Ville, Gabor, and wavelet transforms are useful in highlighting time-frequency features of the signal, the application of such transforms to the monitoring problem requires additional for making decisions concerning the condition of the object being monitored. In particular, the interpretation of the transform coefficients in terms of physical events is essential to making such decisions. We develop a methodology for identifying the physical state of the object based on statistical models of the signals, which could comprise, for example, multiple outputs from devices such as accelerometers, strain sensors and acoustic emission sensors. Classification of machine states based on monitoring signals is performed by comparing likelihood scores for each machine state. We present examples of applying our system to various data, including damped sinusoids and noisy chirps, as a way of illustrating system performance for the case of transient monitoring signals. We compare our system to one which is trained using a DFT-based (non-time-frequency-based) representation (in particular, LPC coefficients) and show that our system exhibits both superior performance as well as greater robustness to noise in the signals.
Download or read book Multiscale Modeling Beyond Wavelets written by Xiaoping Shen and published by Springer. This book was released on 2012-08-31 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is an introduction to the methods that deal with problems raised in using multiscale mathematical/statistical models such as wavelets and other multiscale systems. Special emphasis is given to the applications in filter design, sampling and nonparametric statistical methods for signal modeling, detection and recovering as well as learning and prediction. Applications of these methods notably to signal distortion treatment (Gibbs phenomenon), misisng sample identification, pattern recognition and maching learning problems are discussed and illustrated by examples. Both continuous and sampled (digitized) signals are considered. These methods are in contrast to more traditional methods involving mainly Fourier series withwhich they will also be compared. These multiscale methods have better localization properties, but also avoid excessive oscillations often encountered inboth signal and image analysis.
Download or read book Multiscale Signal Processing written by Albert Benveniste and published by . This book was released on 1990 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "This a short course intended to relate to each other the following topics: multirate filtering and maximally decimated QMF filter banks, multiresolution analysis and multiscale signal analysis and associated wavelet transforms."
Download or read book Multi scale Autoregressive Processes written by Michèle Basseville and published by . This book was released on 1990 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances in Chemical Engineering written by Guy B. Marin and published by Elsevier. This book was released on 2005-10-24 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theme of the present volume "Multiscale Analysis" has been introduced about a decade ago and is now reaching a stage where a first balance can be made and further research directions should be decided. Contributions have been carefully selected to ensure the reader will not be confronted with quantum mechanics at one side of the spectrum nor with chemical plants or even the environment on the other side. Maintaining a strong connection with reality i.e. experimental data was another selection criterion. Experimental validation remains the corner stone of any theoretical development and very powerful experimentel techniques are emerging.Areas covered include discussing in depth an important example of experimental techniques. Coming from the medical world, Magnetic Resonance techniques can now provide even quantitative answers to problems our community is faced with. The modeling issue is discussed further. Finally, the limitations of the classic reactor engineering models are outlined.* Original reviews* Leading chemical engineers as authors* Update on biomaterials use* Novel subject on use of biomaterials in drug delivery and gene therapy* Mathematical modeling
