Multiscale Signal Analysis And Modeling PDF Download
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| Author | : Xiaoping Shen |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 388 |
| Release | : 2012-09-18 |
| Genre | : Technology & Engineering |
| ISBN | : 1461441455 |
Download Multiscale Signal Analysis and Modeling Book in PDF, ePub and Kindle
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.
| Author | : |
| Publisher | : Springer |
| Total Pages | : 398 |
| Release | : 2012-09-19 |
| Genre | : |
| ISBN | : 9781461441465 |
Download Multiscale Signal Analysis and Modeling Book in PDF, ePub and Kindle
| Author | : Kenneth Chien-ko Chou |
| Publisher | : |
| Total Pages | : 265 |
| Release | : 1991 |
| Genre | : Signal processing |
| ISBN | : |
Download A Stochastic Modeling Approach to Multiscale Signal Processing Book in PDF, ePub and Kindle
| Author | : Kenneth Chien-ko Chou |
| Publisher | : |
| Total Pages | : 265 |
| Release | : 1991 |
| Genre | : |
| ISBN | : |
Download A Stochastic Modeling Appraoch to Multiscale Signal Processing Book in PDF, ePub and Kindle
| Author | : Kenneth Chien-ko Chou |
| Publisher | : |
| Total Pages | : 530 |
| Release | : 1991 |
| Genre | : |
| ISBN | : |
Download A Stochastic Modelling Approach to Multiscale Signal Processing Book in PDF, ePub and Kindle
| Author | : |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2004 |
| Genre | : |
| ISBN | : |
Download Multiscale Statistical Models for Signal and Image Processing Book in PDF, ePub and Kindle
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.
| Author | : Jianbo Gao |
| Publisher | : John Wiley & Sons |
| Total Pages | : 368 |
| Release | : 2007-12-04 |
| Genre | : Mathematics |
| ISBN | : 0470191643 |
Download Multiscale Analysis of Complex Time Series Book in PDF, ePub and Kindle
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.
| Author | : Vittorio Cristini |
| Publisher | : Cambridge University Press |
| Total Pages | : 299 |
| Release | : 2010-09-09 |
| Genre | : Technology & Engineering |
| ISBN | : 1139491504 |
Download Multiscale Modeling of Cancer Book in PDF, ePub and Kindle
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.
| Author | : Jieqian He |
| Publisher | : |
| Total Pages | : 160 |
| Release | : 2021 |
| Genre | : Electronic dissertations |
| ISBN | : |
Download Generative Signal Processing Through Multilayer Multiscale Wavelet Models Book in PDF, ePub and Kindle
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.
| Author | : |
| Publisher | : |
| Total Pages | : 15 |
| Release | : 2007 |
| Genre | : |
| ISBN | : |
Download Multiscale Analysis, Modeling, and Processing of Higher-Dimensional Geometric Data Book in PDF, ePub and Kindle
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.
