{"product_id":"time-frequency-and-wavelets-in-biomedical-signal-processing-isbn-9780780311473","title":"Time Frequency and Wavelets in Biomedical Signal Processing","description":"Brimming with top articles from experts in signal processing and biomedical engineering, \u003ci\u003eTime Frequency and Wavelets in Biomedical Signal Processing\u003c\/i\u003e introduces time-frequency, time-scale, wavelet transform methods, and their applications in biomedical signal processing. This edited volume incorporates the most recent developments in the field to illustrate thoroughly how the use of these time-frequency methods is currently improving the quality of medical diagnosis, including technologies for assessing pulmonary and respiratory conditions, EEGs, hearing aids, MRIs, mammograms, X rays, evoked potential signals analysis, neural networks applications, among other topics.  \u003cp\u003e\u003ci\u003eTime Frequency and Wavelets in Biomedical Signal Processing\u003c\/i\u003e will be of particular interest to signal processing engineers, biomedical engineers, and medical researchers.\u003c\/p\u003e \u003cp\u003eTopics covered include:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eTime-frequency analysis methods and biomedical applications\u003c\/li\u003e \u003cli\u003eWavelets, wavelet packets, and matching pursuits and biomedical applications\u003c\/li\u003e \u003cli\u003eWavelets and medical imaging\u003c\/li\u003e \u003cli\u003eWavelets, neural networks, and fractals\u003c\/li\u003e \u003c\/ul\u003e  List of Contributors.  \u003cp\u003ePreface.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eTIME-FREQUENCY ANALYSIS METHODS WITH BIOMEDICAL APPLICATIONS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eRecent Advances in Time-Frequency Representations: SomeTheoretical Foundation (\u003ci\u003eW. Williams\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eBiological Applications and Interpretations of Time-Frequency Signal Analysis (\u003ci\u003eW. Williams\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eThe Application of Advanced Time-Frequency Analysis Techniques to Doppler Ultrasound (\u003ci\u003eS. Marple, et al.\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eAnalysis of ECG Late Potentials Using Time-Frequency Methods (\u003ci\u003eH. Dickhaus \u0026amp; H. Heinrich\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eTime-Frequency Distributions Applied to Uterine EMG: Characterization and Assessment (\u003ci\u003eJ. Duchene \u0026amp; D. Devedeux\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eTime-Frequency Analyses of the Electrogastrogram (\u003ci\u003eZ. Lin and J. Chen\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eRecent Advances in Time-Frequency and Time-Scale Methods (\u003ci\u003eC. Mello \u0026amp; M. Akay\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eWAVELETS, WAVELET PACKETS, AND MATCHING PURSUITS WITH BIOMEDICAL APPLICATIONS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eFast Algorithms for Wavelet Transform Computation (\u003ci\u003eO. Rioul \u0026amp; P. Duhamel\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eAnalysis of Cellular Vibrations in the Living Cochlea Using the Continuous Wavelet Transform and the Short-Time Fourier Transform (\u003ci\u003eM. Teich, et al.\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eAlterative Processing Method Using Gabor Wavelets and the Wavelet Transform for the Analysis of Phonocardiogram Signals (\u003ci\u003eM. Matalgah, et al.\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eWavelet Feature Extraction from Neurophysiological Signals (\u003ci\u003eM. Sun \u0026amp; R. Sclabassi\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eExperiments with Adapted Wavelet De-Noising for Medical Signals and Images (\u003ci\u003eR. Coifman \u0026amp; M. Wickerhauser\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eSpeech Enhancement for Hearing Aids (\u003ci\u003eJ. Rutledg\u003c\/i\u003ee).\u003c\/p\u003e \u003cp\u003eFrom Continuous Wavelet Transform to Wavelet Packets: Application to the Estimation of Pulmonary Microvascular Pressure (\u003ci\u003eM. Karrakchou \u0026amp; M. Kunt\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eIn Pursuit of Time-Frequency Representation of Brain Signals (\u003ci\u003eP. Durka \u0026amp; K. Blinowska\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eEEG Spike Directors Based on Different Decompositions: A Comparative Study (\u003ci\u003eL. Senhadji, et al.\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eWAVELETS AND MEDICAL IMAGING.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA Discrete Dyadic Wavelet Transform for Multidimensional Feature Analysis (\u003ci\u003eI. Koren \u0026amp; A. Laine\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eHexagonal QMF Banks and Wavelets (\u003ci\u003eS. Schuler \u0026amp; A. Laine\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eInversion of the Radon Transform under Wavelet Constraints (\u003ci\u003eB. Sahiner \u0026amp; A. Yagle\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eWavelets Applied to Mammograms (\u003ci\u003eW. Richardson\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eHybrid Wavelet Transform for Image Enhancement forComputer-Assisted Diagnosis and Telemedicine Applications (\u003ci\u003eL. Clarke, et al.\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eMedical Image Enhancement Using Wavelet Transform and Arithmetic Coding (\u003ci\u003eP. Saipetch, et al.\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eAdapted Wavelet Encoding in Functional Magnetic Resonance Imaging (\u003ci\u003eD. Healy, et al.\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eA Tutorial Overview of a Stabilization Algorithm for Limited-Angle Tomography (\u003ci\u003eT. Olson\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eWavelet Compression of Medical Images (\u003ci\u003eA. Manduca\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eWAVELETS, NEURAL NETWORKS, AND FRACTALS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSingle Side Scaling Wavelet Frame and Neural Network (\u003ci\u003eQ. Zhang\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eAnalysis of Evoked Potentials Using Wavelet Networks (\u003ci\u003eH. Heinrich \u0026amp; H. Dickhaus\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eSelf-Organizing Wavelet-Based Neural Networks (\u003ci\u003eK. Kobayashi\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eOn Wavelets and Fractal Processes (\u003ci\u003eP. Flandrin\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eFractal Analysis of Heart Rate Variability (\u003ci\u003eR. Fischer \u0026amp; M. Akay\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003eIndex.\u003c\/p\u003e \u003cp\u003eEditor's Biography.\u003c\/p\u003e \u003cb\u003eMetin Akay\u003c\/b\u003e is IEEE Press Series Editor for the IEEE Press Series in Biomedical Engineering, and a member of the IEEE Engineering in Medicine and Biology Society Publication Committee. Dr. Akay has authored Biomedical Signal Processing (Academic Press, 1994); Detection and Estimation of Biomedical Signals (Academic Press, 1996); and coauthored the most recent edition of Theory and Design of Biomedical Instruments (Academic Press, 1991). He has published a number of technical papers in the areas of noninvasive detection of coronary artery disease, early human development, and control of breathing. In addition, Dr. Akay holds two U.S. patents and has given several keynote\/plenary and invited talks at international conferences, workshops, and symposiums in these areas.  Biomedical Engineering Time Frequency and Wavelets in Biomedical Signal Processing IEEE Press Series in Biomedical Engineering Metin Akay, Series Editor Endorsed by the IEEE Engineering in Medicine and Biology Society Brimming with top articles from experts in signal processing and biomedical engineering, Time Frequency and Wavelets in Biomedical Signal Processing introduces time-frequency, time-scale, wavelet transform methods, and their applications in biomedical signal processing. This edited volume incorporates the most recent developments in the field to illustrate thoroughly how the use of these time-frequency methods is currently improving the quality of medical diagnosis, including technologies for assessing pulmonary and respiratory conditions, EEGs, hearing aids, MRIs, mammograms, X rays, evoked potential signals analysis, neural networks applications, among other topics. Time Frequency and Wavelets in Biomedical Signal Processing will be of particular interest to signal processing engineers, biomedical engineers, and medical researchers. Topics covered include: \u003cul\u003e \u003cli\u003eTime-frequency analysis methods and biomedical applications\u003c\/li\u003e \u003cli\u003eWavelets, wavelet packets, and matching pursuits and biomedical applications\u003c\/li\u003e \u003cli\u003eWavelets and medical imaging\u003c\/li\u003e \u003cli\u003eWavelets, neural networks, and fractals\u003c\/li\u003e \u003c\/ul\u003e","brand":"Wiley-IEEE Press","offers":[{"title":"Default Title","offer_id":47990391341285,"sku":"NP9780780311473","price":299.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780780311473.jpg?v=1761787639","url":"https:\/\/k12savings.com\/es\/products\/time-frequency-and-wavelets-in-biomedical-signal-processing-isbn-9780780311473","provider":"K12savings","version":"1.0","type":"link"}