Application of Dual-Tree Complex Wavelet Transforms to Burst Detection and RF Fingerprint Classification

Language: English

Published by Creative Media Partners, LLC Mai 2025, 2025

1025132785 / 9781025132785

  • Hardcover
  • New
See all details

Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

5-star seller

AbeBooks seller since August 14, 2006

View this seller's items
Hardcover

Condition: New

US$ 52.16

US$ 72.07 shipping 
Ships from Germany to U.S.A.

Quantity: 2 available

Add to basket
Free 30-day returns

Item description from seller

Neuware - This work addresses various Open Systems Interconnection (OSI) Physical (PHY) layer mechanisms to extract and exploit RF waveform features ('fingerprints') that are inherently unique to specific devices and that may be used to provide hardware specific identification(manufacturer, model, and/or serial number). This is addressed by applying a Dual-Tree Complex Wavelet Transform (DT-CWT) to improve burst detection and RF fingerprint classification. A 'Denoised VT' technique is introduced to improve performance at lower SNRs, with denoising implemented using a DT-CWT decomposition prior to Traditional VT processing. A newly developed Wavelet Domain (WD) fingerprinting technique is presented using statistical WD fingerprints with Multiple Discriminant Analysis/Maximum Likelihood (MDA/ML) classification.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

Seller Inventory # 9781025132785

Title
Application of Dual-Tree Complex Wavelet Transforms to Burst Detection and RF Fingerprint Classification
Author
Randall W Klein
Publisher
Creative Media Partners, LLC Mai 2025
Publication year
2025
Condition
Neu
Binding
Buch
Language
English
ISBN 10
1025132785
ISBN 13
9781025132785
Item weight
390 grams
Dimensions
234x156x10 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

Item30 to 40 business days7 to 14 business days
First itemUS$ 72.07US$ 83.71
Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.

Payment methods

  • Visa
  • Mastercard
  • American Express
  • Apple Pay
  • Google Pay
  • Bank Wire Transfer
  • Check
  • Paypal

Store description

Das Unternehmen AHA-BUCH GmbH: Seit der Gründung von AHA-BUCH im Juli 2005 ist unser Hauptziel, zufriedenen Kunden so schnell und so preisgünstig wie möglich ihren Bücherwunsch zu erfüllen. Unsere Firma beschäftigt 16 Mitarbeiter, die nur ein Ziel kennen: den Kunden und seine Wünsche! Auf über 3700 m2 Fläche haben wir über 100.000 Bücher, Modernes Antiquariat und Spiele auf Lager.

Specialty

Kinderbücher & Kinderhör Casetten, German Books, Software, Natur & Tiere, Ratgeber, Sachbücher, Englische Bücher, Medizin & Gesundheit, Universität & Studium

Seller's business information

AHA-BUCH GmbH

Garlebsen 48
Einbeck, Germany 37574