LEADER 05224nam 22006614a 450 001 9910143688103321 005 20170815123636.0 010 $a1-280-72165-0 010 $a9786610721658 010 $a0-470-08780-3 010 $a0-470-08779-X 035 $a(CKB)1000000000356621 035 $a(EBL)281846 035 $a(OCoLC)476027142 035 $a(SSID)ssj0000108024 035 $a(PQKBManifestationID)11138201 035 $a(PQKBTitleCode)TC0000108024 035 $a(PQKBWorkID)10017657 035 $a(PQKB)11139817 035 $a(MiAaPQ)EBC281846 035 $a(EXLCZ)991000000000356621 100 $a20060523d2006 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aAutonomous software-defined radio receivers for deep space applications$b[electronic resource] /$fedited by Jon Hamkins and Marvin K. Simon 210 $aHoboken, N.J. $cWiley-Interscience$dc2006 215 $a1 online resource (459 p.) 225 1 $aDeep-space communications and navigation series 300 $aDescription based upon print version of record. 311 $a0-470-08212-7 320 $aIncludes bibliographical references and index. 327 $aAutonomous Software-Defined Radio Receivers for Deep Space Applications; Table of Contents; Foreword; Preface; Acknowledgments; Contributors; Chapter 1: Introduction and Overview; 1.1 Preliminaries; 1.1.1 Signal Model; 1.1.2 Anatomy of the Received Signal; 1.2 Radio Receiver Architectures; 1.2.1 A Conventional Radio Receiver; 1.2.2 Electra; 1.2.3 An Autonomous Radio; 1.3 Estimators and Classifiers of the Autonomous Radio; 1.3.1 Carrier Phase Tracking; 1.3.2 Modulation Classification; 1.3.3 Signal-to-Noise Ratio Estimation; 1.3.4 Frequency Tracking 327 $a1.4 An Iterative Message-Passing Architecture1.4.1 Messages from the Symbol-Timing Estimator; 1.4.2 Messages from the Phase Tracker; 1.4.3 Messages from the Modulation Classification; 1.4.4 Messages from the Decoder; 1.5 A Demonstration Testbed; References; Chapter 2: The Electra Radio; 2.1 Electra Receiver Front-End Processing; 2.1.1 AGC; 2.1.2 ADC; 2.1.3 Digital Downconversion and Decimation; 2.2 Electra Demodulation; 2.2.1 Frequency-Acquisition and Carrier-Tracking Loop; 2.2.2 Navigation: Doppler Phase Measurement; 2.2.3 Symbol-Timing Recovery 327 $a2.2.4 Viterbi Node Sync and Symbol SNR Estimation2.3 Electra Digital Modulator; References; Chapter 3: Modulation Index Estimation; 3.1 Coherent Estimation; 3.1.1 BPSK; 3.1.2 M-PSK; 3.2 Noncoherent Estimation; 3.3 Estimation in the Absence of Knowledge of the Modulation, Data Rate, Symbol Timing, and SNR; 3.4 Noncoherent Estimation in the Absence of Carrier Frequency Knowledge; Chapter 4: Frequency Correction; 4.1 Frequency Correction for Residual Carrier; 4.1.1 Channel Model; 4.1.2 Optimum Frequency Estimation over an AWGN Channel 327 $a4.1.3 Optimum Frequency Estimation over a Raleigh Fading Channel4.1.4 Open-Loop Frequency Estimation; 4.1.5 Closed-Loop Frequency Estimation; 4.2 Frequency Correction for Known Data-Modulated Signals; 4.2.1 Channel Model; 4.2.2 Open-Loop Frequency Estimation; 4.2.3 Closed-Loop Frequency Estimation; 4.3 Frequency Correction for Modulated Signals with Unknown Data; 4.3.1 Open-Loop Frequency Estimation; 4.3.2 Closed-Loop Frequency Estimation; References; Chapter 5: Data Format and Pulse Shape Classification; 5.1 Coherent Classifiers of Data Format for BPSK 327 $a5.1.1 Maximum-Likelihood Coherent Classifier of Data Format for BPSK5.1.2 Reduced-Complexity Data Format BPSK Classifiers; 5.1.3 Probability of Misclassification for Coherent BPSK; 5.2 Coherent Classifiers of Data Format for QPSK; 5.2.1 Maximum-Likelihood Coherent Classifier of Data Format for QPSK; 5.2.2 Reduced-Complexity Data Format QPSK Classifiers; 5.2.3 Probability of Misclassification for Coherent QPSK; 5.3 Noncoherent Classification of Data Format for BPSK; 5.3.1 Maximum-Likelihood Noncoherent Classifier of Data Format for BPSK 327 $a5.3.2 Probability of Misclassification for Noncoherent BPSK 330 $aThis book introduces the reader to the concept of an autonomous software-defined radio (SDR) receiver. Each distinct aspect of the design of the receiver is treated in a separate chapter written by one or more leading innovators in the field. Chapters begin with a problem statement and then offer a full mathematical derivation of an appropriate solution, a decision metric or loop-structure as appropriate, and performance results. 410 0$aDeep-space communications and navigation series. 606 $aAstronautics$xCommunication systems 606 $aSoftware radio 608 $aElectronic books. 615 0$aAstronautics$xCommunication systems. 615 0$aSoftware radio. 676 $a621.384197 676 $a629.4743 701 $aHamkins$b Jon$f1968-$0921824 701 $aSimon$b Marvin Kenneth$f1939-$0285778 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910143688103321 996 $aAutonomous software-defined radio receivers for deep space applications$92068283 997 $aUNINA LEADER 03664nam 2200841z- 450 001 9910585942503321 005 20220812 035 $a(CKB)5600000000483056 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/91207 035 $a(oapen)doab91207 035 $a(EXLCZ)995600000000483056 100 $a20202208d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aComputational Intelligence Application in Electrical Engineering 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (174 p.) 311 08$a3-0365-4695-2 311 08$a3-0365-4696-0 330 $aThe Special Issue "Computational Intelligence Application in Electrical Engineering" deals with the application of computational intelligence techniques in various areas of electrical engineering. The topics of computational intelligence applications in smart power grid optimization, power distribution system protection, and electrical machine design and control optimization are presented in the Special Issue. The co-simulation approach to metaheuristic optimization methods and simulation tools for a power system analysis are also presented. The main computational intelligence techniques, evolutionary optimization, fuzzy inference system, and an artificial neural network are used in the research presented in the Special Issue. The articles published in this issue present the recent trends in computational intelligence applications in the areas of electrical engineering. 606 $aHistory of engineering & technology$2bicssc 606 $aTechnology: general issues$2bicssc 610 $aactive distribution network 610 $aadvanced distribution system optimization 610 $aant colony optimization 610 $aco-simulation 610 $acomputational efficiency 610 $acomputational intelligence 610 $acomputational intelligence techniques 610 $adistributed generation 610 $aefficiency factor 610 $aelectric markets 610 $afuzzy logic control 610 $ahigh order newton-like method 610 $ainduction machine 610 $aline-start synchronous motor 610 $ametaheuristic 610 $aMonte Carlo simulations 610 $an/a 610 $aNewton-Raphson 610 $aoptimal allocation and control 610 $aoptimal distribution system management 610 $aoptimal Smart Grid management 610 $aoptimization algorithms 610 $aoptometric analysis 610 $aovercurrent relays 610 $aphotovoltaic generation 610 $apower factor 610 $apower flow 610 $apower system protection 610 $apredictive current control 610 $aprotection relays 610 $arenewable distributed generation 610 $aS-iteration process 610 $aschool-based optimizer 610 $aSmart Grid optimization 610 $aTakagi-Sugeno 610 $atransient models 615 7$aHistory of engineering & technology 615 7$aTechnology: general issues 700 $aBarukc?ic?$b Marinko$4edt$01332315 702 $aRaic?evic?$b Nebojs?a$4edt 702 $aS?arac$b Vasilija$4edt 702 $aBarukc?ic?$b Marinko$4oth 702 $aRaic?evic?$b Nebojs?a$4oth 702 $aS?arac$b Vasilija$4oth 906 $aBOOK 912 $a9910585942503321 996 $aComputational Intelligence Application in Electrical Engineering$93040820 997 $aUNINA