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Signal Processing Noise
Contributor(s): Tuzlukov, Vyacheslav (Author)
ISBN: 0849310253     ISBN-13: 9780849310256
Publisher: CRC Press
OUR PRICE:   $332.50  
Product Type: Hardcover
Published: April 2002
Qty:
Temporarily out of stock - Will ship within 2 to 5 weeks
Annotation: Featuring the results of the author's own research, this book presents a generalized approach to signal processing in multiplicative and additive noise that represents a great leap forward in signal processing and detection theory. It reviews theories particularly useful in practice and describes new approaches to the relevant statistical theory. The text is filled with examples and applications, and each chapter contains an analysis of recent observations obtained by computer modelling and experiments. Addressing a fundamental problem in complex signal processing systems, this book offers the possibility of raising the potential noise immunity in a wide range of applications.
Additional Information
BISAC Categories:
- Technology & Engineering | Telecommunications
- Computers
- Technology & Engineering | Electrical
Dewey: 621.382
LCCN: 2002017487
Series: Electrical Engineering & Applied Signal Processing
Physical Information: 1.52" H x 6.52" W x 9.6" (2.38 lbs) 684 pages
 
Descriptions, Reviews, Etc.
Publisher Description:

Additive and multiplicative noise in the information signal can significantly limit the potential of complex signal processing systems, especially when those systems use signals with complex phase structure. During the last few years this problem has been the focus of much research, and its solution could lead to profound improvements in applications of complex signals and coherent signal processing.

Signal Processing Noise sets forth a generalized approach to signal processing in multiplicative and additive noise that represents a remarkable advance in signal processing and detection theory. This approach extends the boundaries of the noise immunity set by classical and modern signal processing theories, and systems constructed on this basis achieve better detection performance than that of systems currently in use. Featuring the results of the author's own research, the book is filled with examples and applications, and each chapter contains an analysis of recent observations obtained by computer modelling and experiments.

Tables and illustrations clearly show the superiority of the generalized approach over both classical and modern approaches to signal processing noise. Addressing a fundamental problem in complex signal processing systems, this book offers not only theoretical development, but practical recommendations for raising noise immunity in a wide range of applications.