Time-Frequency Signal Analysis and Processing: A Comprehensive Reference
View/ Open
Publisher version (Check access options)
Check access options
Date
2015Author
Boashash, BoualemMetadata
Show full item recordAbstract
Time-Frequency Signal Analysis and Processing (TFSAP) is a collection of theory, techniques and algorithms used for the analysis and processing of non-stationary signals, as found in a wide range of applications including telecommunications, radar, and biomedical engineering. This book gives the university researcher and R&D engineer insights into how to use TFSAP methods to develop and implement the engineering application systems they require. New to this edition: New sections on Efficient and Fast Algorithms; a "Getting Started" chapter enabling readers to start using the algorithms on simulated and real examples with the TFSAP toolbox, compare the results with the ones presented in the book and then insert the algorithms in their own applications and adapt them as needed. Two new chapters and twenty three new sections, including updated references. New topics including: efficient algorithms for optimal TFDs (with source code), the enhanced spectrogram, time-frequency modelling, more mathematical foundations, the relationships between QTFDs and Wavelet Transforms, new advanced applications such as cognitive radio, watermarking, noise reduction in the time-frequency domain, algorithms for Time-Frequency Image Processing, and Time-Frequency applications in neuroscience (new chapter). A comprehensive tutorial introduction to Time-Frequency Signal Analysis and Processing (TFSAP), accessible to anyone who has taken a first course in signals. Key advances in theory, methodology and algorithms, are concisely presented by some of the leading authorities on the respective topics. Applications written by leading researchers showing how to use TFSAP methods.
Collections
- Electrical Engineering [2703 items ]
Related items
Showing items related by title, author, creator and subject.
-
Time-frequency signal and image processing of non-stationary signals with application to the classification of newborn EEG abnormalities
Boashash, Boualem; Boubchir, Larbi; Azemi, Ghasem ( IEEE , 2011 , Conference)This paper presents an introduction to time-frequency (T-F) methods in signal processing, and a novel approach for EEG abnormalities detection and classification based on a combination of signal related features and image ... -
Estimating the number of components of a multicomponent nonstationary signal using the short-term time-frequency Rényi entropy
Sucic, Victor; Saulig, Nicoletta; Boashash, Boualem ( Springer , 2011 , Article)The time-frequency Rényi entropy provides a measure of complexity of a nonstationary multicomponent signal in the time-frequency plane. When the complexity of a signal corresponds to the number of its components, then this ... -
Instantaneous frequency based newborn EEG seizure characterisation
Mesbah M.; O'Toole J.M.; Colditz P.B.; Boashash B. (2012 , Article)The electroencephalogram (EEG), used to noninvasively monitor brain activity, remains the most reliable tool in the diagnosis of neonatal seizures. Due to their nonstationary and multi-component nature, newborn EEG seizures ...