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This final year/postgraduate text for courses in digital filters or digital signal processing deals with the construction of algorithms that filter data into useful information. It starts with the basics and goes on to cover advanced topics such as recursive and non-recursive filters (including optimization techniques), wave digital filters and DFTs. A new chapter on the application of digital signal processing offers up-to-date techniques and there are new problems and examples throughout. A solutions manual is available (0-07-002122-8). Other features new to this second edition include chapters on quasi-Newton and minimax optimization algorithms for the design of recursive filters and equalizers, and efficient and robust algorithms for the design of nonrecursive filters and differentiators. HLP computer language is now replaced with Pascal.
This text investigates the mathematical construction and algorithmic implementation of digital filters to transform raw data into actionable information. Andreas Antoniou, a recognized authority in signal processing, provides a structured pedagogical framework for students and practitioners. The book utilizes a progression from fundamental signal theory to complex optimization techniques, supported by rigorous mathematical proofs and practical design examples.
What You Will Find
Scope Limits
Experts identify this work as a foundational academic resource for advanced undergraduate and graduate-level signal processing curricula. Readers frequently note the technical density of the prose and the necessity of a strong background in linear systems to fully utilize the provided algorithms.
Page Count:
524
Publication Date:
1979-01-01
Publisher:
McGraw-Hill Companies
ISBN-10:
0070021171
ISBN-13:
9780070021174
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