LEADER 04472nam 2201057z- 450 001 9910557127903321 005 20231214133244.0 035 $a(CKB)5400000000040775 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/68670 035 $a(EXLCZ)995400000000040775 100 $a20202105d2020 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aOptics for AI and AI for Optics 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2020 215 $a1 electronic resource (162 p.) 311 $a3-03936-398-0 311 $a3-03936-399-9 330 $aArtificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today?s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today?s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields. 606 $aHistory of engineering & technology$2bicssc 610 $alight emitting diode 610 $anonlinearity estimation and compensation 610 $aprobabilistic Bayesian learning 610 $avisible light communication 610 $adigital signal processing 610 $asupport vector machines 610 $aBCSVM 610 $anonlinear equalization 610 $acoherent detection 610 $ak-nearest neighbor algorithm 610 $amodulation format identification 610 $aOSNR monitoring 610 $aneural networks 610 $aoptical communications 610 $aoptimization 610 $aequalizer 610 $atap estimation 610 $aoptical Fast-OFDM 610 $anonlinearity compensation 610 $aoptical fiber communications 610 $achromatic dispersion 610 $ashort-reach communication 610 $aneural network 610 $ahybrid signal processing 610 $afiber optics communications 610 $acoherent communications 610 $amachine learning 610 $aclustering 610 $anonlinearity cancellation 610 $aentanglement 610 $acharge qubit 610 $aposition-based semiconductor qubits 610 $acryogenic technologies 610 $asemiconductor photon communication 610 $aJaynes-Cummings-Hubbard formalism 610 $adeep neural networks 610 $avolterra equalization 610 $anonlinear systems 610 $acoherent optical communication 610 $apassive optical networks 610 $anonlinear compensation 610 $aoptical transmission 610 $aoptical networks 610 $aartificial intelligence 610 $aquality of transmission 610 $aoptical performance monitoring 610 $afailure management 610 $aartificial neural networks 610 $adeep neural network 610 $aimage classification 610 $aphotonic integrated circuits 610 $asemiconductor optical amplifiers 610 $aphotonic neural network 615 7$aHistory of engineering & technology 700 $aWei$b Jinlong$4edt$01291777 702 $aTao Lau$b Alan Pak$4edt 702 $aYi$b Lilin$4edt 702 $aGiacoumidis$b Elias$4edt 702 $aCheng$b Qixiang$4edt 702 $aWei$b Jinlong$4oth 702 $aTao Lau$b Alan Pak$4oth 702 $aYi$b Lilin$4oth 702 $aGiacoumidis$b Elias$4oth 702 $aCheng$b Qixiang$4oth 906 $aBOOK 912 $a9910557127903321 996 $aOptics for AI and AI for Optics$93021910 997 $aUNINA