Positioning and Navigation Using Machine Learning Methods (Registro nro. 276446)

MARC details
000 -LIDER
fixed length control field 03678nam a22005535i 4500
001 - CONTROL NUMBER
control field 978-981-97-6199-9
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250516160139.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240917s2024 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789819761999
-- 978-981-97-6199-9
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TK5101-5105.9
072 #7 - SUBJECT CATEGORY CODE
Subject category code TJK
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code TEC041000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code TJK
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 621.382
Edition number 23
245 10 - TITLE STATEMENT
Title Positioning and Navigation Using Machine Learning Methods
Medium [electronic resource] /
Statement of responsibility, etc. edited by Kegen Yu.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2024.
264 #1 -
-- Singapore :
-- Springer Nature Singapore :
-- Imprint: Springer,
-- 2024.
300 ## - PHYSICAL DESCRIPTION
Extent X, 374 p. 187 illus., 153 illus. in color.
Other physical details online resource.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
490 1# - SERIES STATEMENT
Series statement Navigation: Science and Technology,
International Standard Serial Number 2522-0462 ;
Volume/sequential designation 14
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Chapter 1. Introduction -- Chapter 2. Indoor localization using ranging model constructed with BP neural network -- Chapter 3. Classification of signal propagation channel using CNN and wavelet packet analysis -- Chapter 4. Semi supervised indoor localization -- Chapter 5. Unsupervised learning for practical indoor localization -- Chapter 6. Deep learning based PDR localization using smartphone sensors and GPS data -- Chapter 7. Deductive reinforcement learning for vehicle navigation -- Chapter 8. Privacy preserving aggregation for federated learning based navigation -- Chapter 9. Learning enhanced INS/GPS integrated navigation -- Chapter 10. UAV localization using deep supervised learning and reinforcement learning -- Chapter 11. Learning based UAV path planning with collision avoidance -- Chapter 12. Learning assisted navigation for planetary rovers -- Chapter 13. Improved planetary rover localization using slip based autonomous ZUPT.
520 ## - SUMMARY, ETC.
Summary, etc. This is the first book completely dedicated to positioning and navigation using machine learning methods. It deals with ground, aerial, and space positioning and navigation for pedestrians, vehicles, UAVs, and LEO satellites. Most of the major machine learning methods are utilized, including supervised learning, unsupervised learning, deep learning, and reinforcement learning. The book presents both fundamentals and in-depth studies as well as practical examples in positioning and navigation. Extensive data processing and experimental results are provided in the major chapters through conducting experimental campaigns or using in-situ measurements.
541 ## - IMMEDIATE SOURCE OF ACQUISITION NOTE
Owner UABC ;
Method of acquisition Perpetuidad
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Telecommunication.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Machine learning.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Signal processing.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Communications Engineering, Networks.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Machine Learning.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Signal, Speech and Image Processing.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Yu, Kegen.
Relator term editor.
-- (orcid)0000-0001-7710-3073
-- https://orcid.org/0000-0001-7710-3073
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9789819761982
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9789819762002
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9789819762019
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Navigation: Science and Technology,
-- 2522-0462 ;
Volume number/sequential designation 14
856 40 - ELECTRONIC LOCATION AND ACCESS
Public note Libro electrónico
Uniform Resource Identifier http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-981-97-6199-9
912 ## -
-- ZDB-2-ENG
912 ## -
-- ZDB-2-SXE
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Libro Electrónico
Existencias
Estado de retiro Colección Ubicación permanente Ubicación actual Fecha de ingreso Total Checkouts Date last seen Número de copia Tipo de material
  Colección de Libros Electrónicos Biblioteca Electrónica Biblioteca Electrónica 16/05/2025   16/05/2025 1 Libro Electrónico

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