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005 20190328114810.0
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019 _a956678831
020 _a9780128017432
_q(electronic bk.)
020 _a0128017430
_q(electronic bk.)
020 _a133600892X
020 _a9781336008922
020 _z9780128015384
020 _z0128015381 (Trade Paper)
020 _a0128015381
020 _a9780128015384
024 3 _a9780128015384
035 _a(OCoLC)903489055
_z(OCoLC)956678831
050 4 _aTK5102.5
072 7 _aTEC
_x009070
_2bisacsh
082 0 4 _a621.382
_223
245 0 0 _aBio-inspired computation in telecommunications /
_h[electronic resource]
_cedited by Xin-She Yang, Su Fong Chien, Tiew On Ting.
264 1 _aWaltham, MA :
_bElsevier Ltd.,
_c[2015]
264 4 _c�2015
300 _a1 online resource :
_billustrations
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
504 _aIncludes bibliographical references and index.
588 0 _aOnline resource; title from PDF title page (EBSCO, viewed February 19, 2015).
505 0 _aFront Cover; Bio-Inspired Computation in Telecommunications; Copyright ; Contents ; Preface ; List of Contributors ; Chapter 1: Bio-Inspired Computation and Optimization: An Overview; 1.1. Introduction; 1.2. Telecommunications and optimization; 1.3. Key challenges in optimization; 1.3.1. Infinite Monkey Theorem and Heuristicity; 1.3.2. Efficiency of an Algorithm; 1.3.3. How to Choose Algorithms; 1.3.4. Time Constraints; 1.4. Bio-inspired optimization algorithms; 1.4.1. SI-Based Algorithms; 1.4.1.1. Ant and bee algorithms; 1.4.1.2. Bat algorithm; 1.4.1.3. Particle swarm optimization.
505 8 _a1.4.1.4. Firefly algorithm1.4.1.5. Cuckoo search; 1.4.2. Non-SI-Based Algorithms; 1.4.2.1. Simulated annealing; 1.4.2.2. Genetic algorithms; 1.4.2.3. Differential evolution; 1.4.2.4. Harmony search; 1.4.3. Other Algorithms; 1.5. Artificial neural networks; 1.5.1. Basic Idea; 1.5.2. Neural Networks; 1.5.3. Back Propagation Algorithm; 1.6. Support vector machine; 1.6.1. Linear SVM; 1.6.2. Kernel Tricks and Nonlinear SVM; 1.7. Conclusions; References; Chapter 2: Bio-Inspired Approaches in Telecommunications; 2.1. Introduction; 2.2. Design problems in telecommunications; 2.3. Green communications.
505 8 _a2.3.1. Energy Consumption in Wireless Communications2.3.2. Metrics for Energy Efficiency; 2.3.3. Radio Resource Management; 2.3.4. Strategic Network Deployment; 2.4. Orthogonal frequency division multiplexing; 2.4.1. OFDM Systems; 2.4.2. Three-Step Procedure for Timing and Frequency Synchronization; 2.5. OFDMA model considering energy efficiency and quality-of-service; 2.5.1. Mathematical Formulation; 2.5.2. Results; 2.6. Conclusions; References; Chapter 3: Firefly Algorithm in Telecommunications; 3.1. Introduction; 3.2. Firefly algorithm; 3.2.1. Algorithm Complexity.
505 8 _a3.2.2. Variants of Firefly Algorithm3.3. Traffic Characterization; 3.3.1. Network Management Based on Flow Analysis and Traffic Characterization; 3.3.2. Firefly Harmonic Clustering Algorithm; 3.3.3. Results; 3.4. Applications in wireless cooperative networks; 3.4.1. Related Work; 3.4.2. System Model and Problem Statement; 3.4.2.1. Energy and spectral efficiencies; 3.4.2.2. Problem statement; 3.4.3. Dinkelbach Method; 3.4.4. Firefly Algorithm; 3.4.5. Simulations and Numerical Results; 3.5. Concluding remarks; 3.5.1. FA in Traffic Characterization; 3.5.2. FA in Cooperative Networks; References.
505 8 _aChapter 4: A Survey of Intrusion Detection Systems Using Evolutionary Computation4.1. Introduction; 4.2. Intrusion detection systems; 4.2.1. IDS Components; 4.2.2. Research Areas and Challenges in Intrusion Detection; 4.3. The method: evolutionary computation; 4.4. Evolutionary computation applications on intrusion detection; 4.4.1. Foundations; 4.4.2. Data Collection; 4.4.3. Detection Techniques and Response; 4.4.3.1. Intrusion detection on conventional networks; 4.4.3.2. Intrusion detection on wireless and resource-constrained networks; 4.4.4. IDS Architecture; 4.4.5. IDS Security.
520 _aBio-inspired computation, especially those based on swarm intelligence, has become increasingly popular in the last decade. Bio-Inspired Computation in Telecommunications reviews the latest developments in bio-inspired computation from both theory and application as they relate to telecommunications and image processing, providing a complete resource that analyzes and discusses the latest and future trends in research directions. Written by recognized experts, this is a must-have guide for researchers, telecommunication engineers, computer scientists and PhD students.
650 0 _aTelecommunication.
650 0 _aNatural computation.
650 7 _aTECHNOLOGY & ENGINEERING
_xMechanical.
_2bisacsh
650 7 _aNatural computation.
_2fast
_0(OCoLC)fst01745866
650 7 _aTelecommunication.
_2fast
_0(OCoLC)fst01145830
650 7 _aBusiness & Economics.
_2hilcc
650 7 _aTransportation Economics.
_2hilcc
650 1 2 _aComputational Biology.
_0(DNLM)D019295
650 1 2 _aTelecommunications.
_0(DNLM)D013685
655 4 _aElectronic books.
700 1 _aYang, Xin-She,
_eeditor.
700 1 _aChien, Su Fong,
_eeditor.
700 1 _aTing, Tiew On,
_eeditor.
776 0 8 _iPrint version:
_tBio-inspired computation in telecommunications.
_dWaltham, MA : Elsevier Ltd., [2015]
_w(DLC) 2014960051
856 4 0 _3ScienceDirect
_uhttp://www.sciencedirect.com/science/book/9780128015384
999 _c247045
_d247045