£110.96

Wiley Regularization and Bayesian Methods for Inverse Problems

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Description

Explore the complexities of ill-posed inverse problems with this specialized text from Wiley. This book addresses challenges in signal and image processing where observed data alone is insufficient for finding solutions. By focusing on the necessity of a priori information, the text explains how building solutions requires recognizing and incorporating specific pieces of external data. Readers will learn how these solutions are shaped by the specific information taken into account. Understanding how to clarify and integrate this information is essential for determining the domain of validity and the practical field of application for various solutions. This work bridges a historical gap in the signal-image community, providing the necessary framework for those working with complex data reconstruction and processing tasks.

Key Features

Focuses on the study of ill-posed inverse problems within signal and image processing environments.

Explains the necessity of using a priori information to build complete solutions from observed data.

Provides guidance on clarifying information to establish the domain of validity for mathematical solutions.

Addresses the application fields for solutions built through specific data integration techniques.

Developed by Wiley-ISTE to serve the needs of the signal and image processing community.

Product Specifications

Brand
Wiley
Format
Hardcover
Domain
Amazon UK
Release Date
06 February 2015
Listed Since
05 June 2013

Barcode

No barcode data available

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