Cited by 274Digital Filter Design and ImplementationMathematical Analysis and Transform MethodsAdvanced Data Compression Techniques

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Fast Algorithms for Signal Processing

Blahut, Richard E.·2010·Cambridge University Press eBooks

DOI 10.1017/cbo9780511760921

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Abstract

Efficient signal processing algorithms are important for embedded and power-limited applications since, by reducing the number of computations, power consumption can be reduced significantly. Similarly, efficient algorithms are also critical to very large scale applications such as video processing and four-dimensional medical imaging. This self-contained guide, the only one of its kind, enables engineers to find the optimum fast algorithm for a specific application. It presents a broad range of computationally-efficient algorithms, describes their structure and implementation, and compares their relative strengths for given problems. All the necessary background mathematics is included and theorems are rigorously proved, so all the information needed to learn and apply the techniques is provided in one convenient guide. With this practical reference, researchers and practitioners in electrical engineering, applied mathematics, and computer science can reduce power dissipation for low-end applications of signal processing, and extend the reach of high-end applications.

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Authors: Blahut, R. E.
Affiliations: University of Illinois Urbana-Champaign (US)
Corresponding author: Blahut, Richard E.
Venue: Cambridge University Press eBooks
Publisher: Cambridge University Press
Published: 2010-06-24
DOI: 10.1017/cbo9780511760921
OpenAlex: W565312106
Cited by: 274
References: 126
Citations by year: 2026: 13 · 2025: 17 · 2024: 24 · 2023: 20 · 2022: 15 · 2021: 22 · 2020: 27 · 2019: 21 · 2018: 22 · 2017: 14 · 2016: 15 · 2015: 28 · 2014: 12 · 2013: 8 · 2012: 4
FWCI: 1.43
Type: book
Language: en
Open access: closed
Licence: www.cambridge.org/core/terms (unspecified, 313 d)
Locations: Cambridge University Press eBooks (publishedVersion)
CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
Topics: Physical Sciences › Computer Science › Signal Processing › Digital Filter Design and Implementation
Physical Sciences › Mathematics › Applied Mathematics › Mathematical Analysis and Transform Methods
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Data Compression Techniques
Keywords: fast algorithms, computational efficiency, energy consumption reduction, embedded systems, video processing, algorithm comparison

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