| 000 | 04398nam a22005535i 4500 | ||
|---|---|---|---|
| 999 |
_c11722 _d11722 |
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| 001 | 978-3-319-55310-8 | ||
| 003 | DE-He213 | ||
| 005 | 20211207160206.0 | ||
| 008 | 170504s2017 gw | s |||| 0|eng d | ||
| 020 | _a9783319553108 | ||
| 040 | _cAIKTC-KRRC | ||
| 041 | _aENG | ||
| 072 | 7 |
_aUYQ _2bicssc |
|
| 072 | 7 |
_aTEC009000 _2bisacsh |
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| 072 | 7 |
_aUYQ _2thema |
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| 082 | 0 | 4 |
_a006.3 _223 |
| 100 | 1 |
_aYu, Qiang. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
| 245 | 1 | 0 |
_aNeuromorphic Cognitive Systems _h[electronic resource] : _bA Learning and Memory Centered Approach / |
| 250 | _a1st ed. 2017. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2017. |
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| 300 |
_aXIV, 172 p. _bCard Paper |
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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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| 490 | 1 |
_aIntelligent Systems Reference Library, _x1868-4394 ; _v126 |
|
| 520 | _aThis book presents neuromorphic cognitive systems from a learning and memory-centered perspective. It illustrates how to build a system network of neurons to perform spike-based information processing, computing, and high-level cognitive tasks. It is beneficial to a wide spectrum of readers, including undergraduate and postgraduate students and researchers who are interested in neuromorphic computing and neuromorphic engineering, as well as engineers and professionals in industry who are involved in the design and applications of neuromorphic cognitive systems, neuromorphic sensors and processors, and cognitive robotics. The book formulates a systematic framework, from the basic mathematical and computational methods in spike-based neural encoding, learning in both single and multi-layered networks, to a near cognitive level composed of memory and cognition. Since the mechanisms for integrating spiking neurons integrate to formulate cognitive functions as in the brain are little understood, studies of neuromorphic cognitive systems are urgently needed. The topics covered in this book range from the neuronal level to the system level. In the neuronal level, synaptic adaptation plays an important role in learning patterns. In order to perform higher-level cognitive functions such as recognition and memory, spiking neurons with learning abilities are consistently integrated, building a system with encoding, learning and memory functionalities. The book describes these aspects in detail. | ||
| 650 | 0 |
_aComputer Engineering _94622 |
|
| 653 | _aComputational Intelligence. | ||
| 653 | _aArtificial Intelligence. | ||
| 653 | _aNeurosciences. | ||
| 700 | 1 |
_aTang, Huajin. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
| 700 | 1 |
_aHu, Jun. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
| 700 | 1 |
_aTan Chen, Kay. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783319553085 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783319553092 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783319856254 |
| 830 | 0 |
_aIntelligent Systems Reference Library, _x1868-4394 ; _v126 |
|
| 856 | 4 | 0 |
_uhttps://doi.org/10.1007/978-3-319-55310-8 _zClick here to access eBook in Springer Nature platform. (Within Campus only.) |
| 942 |
_cEBOOKS _2ddc |
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