Area preserving deformation of multiresolution curves
Computer Aided Geometric Design
Analysis of M-channel time-varying filter banks
Digital Signal Processing
Statistical analysis of the blood glucose data for automated diagnosis
MCBC'08 Proceedings of the 9th WSEAS International Conference on Mathematics & Computers In Biology & Chemistry
Computers in Biology and Medicine
Spectral analysis of the heart sounds for medical diagnosis
CONTROL'08 Proceedings of the 4th WSEAS/IASME international conference on Dynamical systems and control
Analysis of multicomponent AM-FM signals using FB-DESA method
Digital Signal Processing
Interpolation of signals with missing data using Principal Component Analysis
Multidimensional Systems and Signal Processing
Nonlinear system identification using two-dimensional wavelet-based state-dependent parameter models
International Journal of Systems Science
PCB inspection using image processing and wavelet transform
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Persian sign language (PSL) recognition using wavelet transform and neural networks
Expert Systems with Applications: An International Journal
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications - Volume Part II
PCA positioning sensor characterization for terrain based navigation of UVs
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
A model for the receptive field of retinal ganglion cells
Neural Networks
Fuzzy model identification of dengue epidemic in Colombia based on multiresolution analysis
Artificial Intelligence in Medicine
Digital Signal Processing
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From the Publisher:Signal analysis gives an insight into the properties of signals and stochastic processes by methodology. Linear transforms are integral to the continuing growth of signal processes as they characterize and classify signals. In particular, those transforms that provide time-frequency signal analysis are attracting greater numbers of researchers and are becoming an area of considerable importance. The key characteristic of these transforms, along with a certain time-frequency localization called the wavelet transform and various types of multirate filter banks, is their high computational efficiency. It is this computational efficiently which accounts for their increased application. This book provides a complete overview and introduction to signal analysis. It presents classical and modern signal analysis methods in a sequential structure starting with the background to signal theory. Progressing through the book the author introduces more advanced topics in an easy to understand style. Including recent and emerging topics such as filter banks with perfect reconstruction, time frequency and wavelets. With great accuracy and technical merit, this book makes a useful and original contribution to the current literature.