000 | 03931nam a22005175i 4500 | ||
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001 | 978-3-031-16344-9 | ||
003 | DE-He213 | ||
005 | 20240423125034.0 | ||
007 | cr nn 008mamaa | ||
008 | 230111s2023 sz | s |||| 0|eng d | ||
020 |
_a9783031163449 _9978-3-031-16344-9 |
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024 | 7 |
_a10.1007/978-3-031-16344-9 _2doi |
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_aTJFC _2bicssc |
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_a621.3815 _223 |
245 | 1 | 0 |
_aFrontiers of Quality Electronic Design (QED) _h[electronic resource] : _bAI, IoT and Hardware Security / _cedited by Ali Iranmanesh. |
250 | _a1st ed. 2023. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2023. |
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300 |
_aXX, 679 p. 372 illus., 275 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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505 | 0 | _aChapter 1. NAND Flash Memory Devices Security Enhancement Based on Physical Unclonable Functions -- Chapter 2. ReRAM based Neuromorphic Computing -- Chapter 3. Flash Technology for VLSI Design -- Chapter 4. Non-volatile memory Technologies:Characteristics,Deployment and Research Challenges -- Chapter 5. Data Analytics and Machine Learning for Coverage Closure -- Chapter 6. Cell-Aware Model Generation by Using Machine Learning -- Chapter 7. Neuromorphic Computing: A Path to Artificial Intelligence through Emulating Human Brains -- Chapter 8. AI for Cybersecurity in Distributed Automotive IoT Systems -- Chapter 9. Ultra-low Power Implementation of Neural Networks Using Inverter-based Memristive Crossbars -- Chapter 10. AI based Hardware Security Methods for Internet-of-Things Applications -- Chapter 11. Enabling Edge Computing Using Emerging Memory Technologies: From Device to Architecture -- Chapter 12. IoT Commercial, Industrial Applications and AI-powered IoT -- Chapter 13. Hardware and SystemSecurity - Attacks and Coun- termeasures Against Hardware Trojans -- Chapter 14. FPGA Security: Security Threats from Untrusted FPGA CAD Toolchain -- Chapter 15. DoS Attack Models and Mitigation Frameworks for NoC-based SoCs -- Chapter 16. Defense against security threats with regard to SoC Life Cycle -- Chapter 17. Defect Diagnosis Techniques for Silicon Customer Returns. | |
520 | _aQuality Electronic Design (QED)’s landscape spans a vast region where territories of many participating disciplines and technologies overlap. This book explores the latest trends in several key topics related to quality electronic design, with emphasis on Hardware Security, Cybersecurity, Machine Learning, and application of Artificial Intelligence (AI). The book includes topics in nonvolatile memories (NVM), Internet of Things (IoT), FPGA, and Neural Networks. Discusses state-of-the-art in electronics design process, semiconductor memories, FPGA, hardware security, and cybersecurity; Highlights trends, challenges and solutions; Explores application of Machine Learning and Artificial Intelligence in design. | ||
650 | 0 | _aElectronic circuits. | |
650 | 0 | _aEmbedded computer systems. | |
650 | 0 | _aElectronic circuit design. | |
650 | 1 | 4 | _aElectronic Circuits and Systems. |
650 | 2 | 4 | _aEmbedded Systems. |
650 | 2 | 4 | _aElectronics Design and Verification. |
700 | 1 |
_aIranmanesh, Ali. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031163432 |
776 | 0 | 8 |
_iPrinted edition: _z9783031163456 |
776 | 0 | 8 |
_iPrinted edition: _z9783031163463 |
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-16344-9 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cSPRINGER | ||
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_c173536 _d173536 |