Description
Book SynopsisWith signal processing, we want to identify/characterize various physical processes, such as standard engineering variables (e.g. faults on bearings, dynamic properties of structures), as well as biology phenomena (e.g. genome sequencing), astronomy (e.g. measuring a black hole), social sciences (e.g. the spread of the corona virus) and the like. This book edition covers different topics from signal and information processing, including methods for signal processing, signal processing in medicine, image and video signal processing, and signal processing in engineering.
Table of Contents
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Section 1 Methods for Signal Processing
- Chapter 1 Comparative Study and Analysis of Performances among RNS, DBNS, TBNS and MNS for DSP Applications
- Chapter 2 The Fourier Notation of the Geomagnetic Signals Informative Parameters
- Chapter 3 A Time Dependent Model for Image Denoising
Section 2 Methods for Signal Processing
- Chapter 4 An Efficient Signal Processing Algorithm for Detecting Abnormalities in EEG Signal Using CNN
- Chapter 5 Contribution to S-EMG Signal Compression in 1D by the Combination of the Modified Discrete Wavelet Packet Transform (MDWPT) and the Discrete Cosine Transform (DCT)
- Chapter 6 Improved Guided Image Fusion for Magnetic Resonance and Computed Tomography Imaging
- Chapter 7 A Biologically Inspired Algorithm for Low Energy Clustering Problem in Body Area Network
Section 3 Image and Video Signal Processing
- Chapter 8 Segmentation of Visual Images by Sequential Extracting Homogeneous Texture Areas
- Chapter 9 Deep Learning in Visual Computing and Signal Processing
- Chapter 10 Pre-Processing Images of Public Signage for OCR Conversion
- Chapter 11 A Local Binary Pattern-Based Method for Color and Multicomponent Texture Analysis
Section 4 Engineering Applications of Signal Processing
- Chapter 12 An Adaptive EMD Technique for Induction Motor Fault Detection
- Chapter 13 Nondestructive Testing for Corrosion Evaluation of Metal Under Coating
- Chapter 14 Environment Perception Technologies for Power Transmission Line Inspection Robots
- Chapter 15 Feature Extraction Techniques of Non-Stationary Signals for Fault Diagnosis in Machinery Systems
