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Advanced CMOS Integrated Circuit Design and Application
| Advanced CMOS Integrated Circuit Design and Application |
| Autore | Yang Jong-Ryul |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (198 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
90 nm
analog microelectronics design analog system artificial neural network biomedical device biosensors blocker CMOS CMOS circuit CMOS design CMOS detector CMOS rectifier complex thinking concurrent-mode current source current tail current-input ADC current-reuse current-shaping differential detector IC dynamic threshold cancellation technique educational innovation figure-of-merit flicker noise freeware high power conversion efficiency high SNR higher education image processing imaging SNR injection-locked frequency divider integrated circuit design integrated circuit layout integrated folded-dipole antenna LC tank LC-VCO learning algorithm long channel transistors mask operation medical implanted communication service (MICS) MedRadio memristor crossbar memristor switch microbolometer on-wafer open science orthogonal frequency division modulation (OFDM) phase noise pixel-level ADC power management circuit radar sensor readout circuit RF receiver second-order intermodulation (IM2) short channel transistors signal processing spin memristor sub-terahertz imaging switched-biasing varactor vibration energy harvester VLSI voltage responsivity voltage-controlled oscillator wide dynamic range wideband |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566458003321 |
Yang Jong-Ryul
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Memristors for Neuromorphic Circuits and Artificial Intelligence Applications
| Memristors for Neuromorphic Circuits and Artificial Intelligence Applications |
| Autore | Suñé Jordi |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (244 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
AI
artificial intelligence artificial neural network artificial synapse autocovariance boost-factor adjustment character recognition circuit design compact model cortical neurons crossbar array deep learning networks defect-tolerant spatial pooling electronic synapses emulator Flash memories graphene oxide hardware-based deep learning ICs hierarchical temporal memory laser memristive devices memristor memristor crossbar memristor-CMOS hybrid circuit memristors multiscale modeling neocortex neural network hardware neural networks neuromorphic neuromorphic computing neuromorphic engineering neuromorphic hardware neuromorphic systems neuromorphics optimization OxRAM pattern recognition pavlov reinforcement learning resistive switching RRAM self-organization maps sensory and hippocampal responses simulation spike-timing-dependent plasticity spiking neural network spiking neural networks STDP strongly correlated oxides synapse synaptic device synaptic plasticity synaptic weight temporal pooling time series modeling transistor-like devices variability vertical RRAM wire resistance |
| ISBN | 3-03928-577-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910404090703321 |
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Suñé Jordi
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| MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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