LEADER 03001nam 22004935 450 001 9910150455903321 005 20200706154535.0 010 $a3-319-42784-9 024 7 $a10.1007/978-3-319-42784-3 035 $a(CKB)3710000000943136 035 $a(DE-He213)978-3-319-42784-3 035 $a(MiAaPQ)EBC4738851 035 $a(PPN)197136621 035 $a(EXLCZ)993710000000943136 100 $a20161109d2017 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvanced Sensing Techniques for Cognitive Radio /$fby Guodong Zhao, Wei Zhang, Shaoqian Li 205 $a1st ed. 2017. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017. 215 $a1 online resource (X, 76 p. 39 illus., 26 illus. in color.) 225 1 $aSpringerBriefs in Electrical and Computer Engineering,$x2191-8112 311 $a3-319-42783-0 330 $aThis SpringerBrief investigates advanced sensing techniques to detect and estimate the primary receiver for cognitive radio systems. Along with a comprehensive overview of existing spectrum sensing techniques, this brief focuses on the design of new signal processing techniques, including the region-based sensing, jamming-based probing, and relay-based probing. The proposed sensing techniques aim to detect the nearby primary receiver and estimate the cross-channel gain between the cognitive transmitter and primary receiver. The performance of the proposed algorithms is evaluated by simulations in terms of several performance parameters, including detection probability, interference probability, and estimation error. The results show that the proposed sensing techniques can effectively sense the primary receiver and improve the cognitive transmission throughput. Researchers and postgraduate students in electrical engineering will find this an exceptional resource. 410 0$aSpringerBriefs in Electrical and Computer Engineering,$x2191-8112 606 $aElectrical engineering 606 $aComputer organization 606 $aCommunications Engineering, Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/T24035 606 $aComputer Systems Organization and Communication Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/I13006 615 0$aElectrical engineering. 615 0$aComputer organization. 615 14$aCommunications Engineering, Networks. 615 24$aComputer Systems Organization and Communication Networks. 676 $a621.382 700 $aZhao$b Guodong$4aut$4http://id.loc.gov/vocabulary/relators/aut$0902745 702 $aZhang$b Wei$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aLi$b Shaoqian$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910150455903321 996 $aAdvanced Sensing Techniques for Cognitive Radio$92018055 997 $aUNINA LEADER 04437nam 22007215 450 001 9910760298103321 005 20250807145617.0 010 $a9789819967551 010 $a9819967554 024 7 $a10.1007/978-981-99-6755-1 035 $a(MiAaPQ)EBC30858590 035 $a(Au-PeEL)EBL30858590 035 $a(DE-He213)978-981-99-6755-1 035 $a(CKB)28653784600041 035 $a(OCoLC)1409031681 035 $a(EXLCZ)9928653784600041 100 $a20231102d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData Science and Network Engineering $eProceedings of ICDSNE 2023 /$fedited by Suyel Namasudra, Munesh Chandra Trivedi, Ruben Gonzalez Crespo, Pascal Lorenz 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (525 pages) 225 1 $aLecture Notes in Networks and Systems,$x2367-3389 ;$v791 311 08$aPrint version: Namasudra, Suyel Data Science and Network Engineering Singapore : Springer Singapore Pte. Limited,c2023 9789819967544 327 $aPart 1: Computational Intelligence -- Chapter 1: Evaluation of Hand-crafted Features for the Classification of Spam SMS in Dravidian Languages -- Chapter 2: Training Algorithms for Mixtures of Normalizing Flows -- Chapter 3: Facial Expression Based Music Recommendation System using Deep Learning -- Chapter 4: Exploring Time Series Analysis Techniques for Sales Forecasting -- Chapter 5: Keystroke Dynamics Based Analysis and Classification of Hand Posture using Machine Learning Techniques -- Chapter 6: Teenager Friendly News Classification Using Machine Learning Model -- Chapter 7: Turbulent Particle Swarm Optimization and Genetic Algorithm for Function Maximization -- Chapter 8: An Innovative New Open Computer Vision Framework via Artificial Intelligence with Python -- Chapter 9: Meat Freshness State Prediction using a Novel Fifteen Layered Deep Convolutional Neural Network -- Chapter 10: Object Detection in Autonomous Maritime Vehicles: Comparison between YOLO V8 and EfficientDet. etc. 330 $aThis book includes research papers presented at the International Conference on Data Science and Network Engineering (ICDSNE 2023) organized by the Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, India, during July 21?22, 2023. It includes research works from researchers, academicians, business executives, and industry professionals for solving real-life problems by using the advancements and applications of data science and network engineering. This book covers many advanced topics, such as artificial intelligence (AI), machine learning (ML), deep learning (DL), computer networks, blockchain, security and privacy, Internet of things (IoT), cloud computing, big data, supply chain management, and many more. Different sections of this book are highly beneficial for the researchers, who are working in the field of data science and network engineering. 410 0$aLecture Notes in Networks and Systems,$x2367-3389 ;$v791 606 $aTelecommunication 606 $aArtificial intelligence$xData processing 606 $aArtificial intelligence 606 $aInternet of things 606 $aCooperating objects (Computer systems) 606 $aCommunications Engineering, Networks 606 $aData Science 606 $aArtificial Intelligence 606 $aInternet of Things 606 $aCyber-Physical Systems 615 0$aTelecommunication. 615 0$aArtificial intelligence$xData processing. 615 0$aArtificial intelligence. 615 0$aInternet of things. 615 0$aCooperating objects (Computer systems) 615 14$aCommunications Engineering, Networks. 615 24$aData Science. 615 24$aArtificial Intelligence. 615 24$aInternet of Things. 615 24$aCyber-Physical Systems. 676 $a621.382 700 $aNamasudra$b Suyel$01437818 701 $aTrivedi$b Munesh Chandra$01437819 701 $aCrespo$b Rube?n Gonza?lez$01437820 701 $aLorenz$b Pascal$01437821 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910760298103321 996 $aData Science and Network Engineering$93598671 997 $aUNINA