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Window functions—otherwise known as weighting functions, tapering functions, or apodization functions—are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. Window Functions and their Applications in Signal Processing presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing.
Comprehensively reviewing previous research and recent developments, this book:
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Provides suggestions on how to choose a window function for particular applications
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Discusses Fourier analysis techniques and pitfalls in the computation of the DFT
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Introduces window functions in the continuous-time and discrete-time domains
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Considers two implementation strategies of window functions in the time- and frequency domain
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Explores well-known applications of window functions in the fields of radar, sonar, biomedical signal analysis, audio processing, and synthetic aperture radar
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 Changing Software Development: Learning to Become Agile
“Successful companies have known the importance of continuous change and learning for a long time; this is the first book that describes these concepts in an organic way in the context of software development. A must read for everybody involved in this business.”
Giovanni Asproni, Director, Asprotunity... | | 3D Computer Vision: Efficient Methods and Applications (X.media.publishing)This book provides an introduction to the foundations of three-dimensional computer vision and describes recent contributions to the field. Geometric methods include linear and bundle adjustment based approaches to scene reconstruction and camera calibration, stereo vision, point cloud segmentation, and pose estimation of rigid, articulated, and... | | Kubernetes Microservices with Docker
Start using Kubernetes in complex big data and enterprise applications, including Docker containers. Starting with installing Kubernetes on a single node, the book introduces Kubernetes with a simple Hello example and discusses using environment variables in Kubernetes.
Next, Kubernetes Microservices with... |
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