TY - CHAP A1 - In Kang A2 - Irene Hudson A3 - Andrew Rudge A4 - J. Geoffrey Chase ED1 - Awad Kh. Al - Asmari Y1 - 2013-02-06 PY - 2013 T1 - Density Estimation and Wavelet Thresholding via Bayesian Methods: A Wavelet Probability Band and Related Metrics Approach to Assess Agitation and Sedation in ICU Patients N2 - Discrete Wavelet Transform is a wavelet (DWT) transform that is widely used in numerical and functional analysis. Its key advantage over more traditional transforms, such as the Fourier transform, lies in its ability to offer temporal resolution, i.e. it captures both frequency and location (or time) information. This book presents a succinct compendium of some of the more recent variants of DWTs and their use to come up with solutions to an array of problems transcending the traditional application areas of image/video processing and security to the relatively newer areas of medicine, artificial intelligence, power systems and telecommunications. The first of the two sections of this book contains three chapters devoted to traditional applications of DWTs in digital image compression, copyright protection and video resolution enhancement. The second section, comprising of five chapters, is devoted to variants of the DWT and their applications in humanoid-robot vision systems; modeling and simulation recognition of physiological and behavioral traits through human gait and facial images; assessment of agitation and sedation in intensive care patients; maximization of power control systems; and, finally, in demodulation of FM data in free-space optical control systems. BT - Discrete Wavelet Transforms SP - Ch. 6 UR - https://doi.org/10.5772/52434 DO - 10.5772/52434 SN - PB - IntechOpen CY - Rijeka Y2 - 2021-10-21 ER -