000 | 03035nam a22004935i 4500 | ||
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001 | 978-3-642-39162-0 | ||
003 | DE-He213 | ||
005 | 20200421112219.0 | ||
007 | cr nn 008mamaa | ||
008 | 130816s2014 gw | s |||| 0|eng d | ||
020 |
_a9783642391620 _9978-3-642-39162-0 |
||
024 | 7 |
_a10.1007/978-3-642-39162-0 _2doi |
|
050 | 4 | _aQ342 | |
072 | 7 |
_aUYQ _2bicssc |
|
072 | 7 |
_aCOM004000 _2bisacsh |
|
082 | 0 | 4 |
_a006.3 _223 |
100 | 1 |
_aLiu, Bo. _eauthor. |
|
245 | 1 | 0 |
_aAutomated Design of Analog and High-frequency Circuits _h[electronic resource] : _bA Computational Intelligence Approach / _cby Bo Liu, Georges Gielen, Francisco V. Fern�andez. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2014. |
|
300 |
_aXIII, 235 p. _bonline resource. |
||
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 |
_aStudies in Computational Intelligence, _x1860-949X ; _v501 |
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505 | 0 | _aBasic Concepts and Background -- Fundamentals of Optimization Techniques in Analog IC Sizing -- High-Performance Analog IC Sizing: Advanced Constraint Handling and Search Methods -- Analog Circuit Sizing with Fuzzy Specifications: Addressing Soft Constraints -- Process Variation-aware Analog Circuit Sizing: Uncertain Optimization -- Ordinal Optimization-based Methods for Efficient Variation-aware Analog IC Sizing -- Electromagnetic Design Automation: Surrogate Model Assisted Evolutionary Algorithm -- Passive Components Synthesis at High Frequencies: Handling Prediction Uncertainty -- mm-Wave Linear Amplifier Design Automation: A First Step to Complex Problems -- mm-Wave Nonlinear IC and Complex Antenna Synthesis: Handling High Dimensionality. | |
520 | _aComputational intelligence techniques are becoming more and more important for automated problem solving nowadays. Due to the growing complexity of industrial applications and the increasingly tight time-to-market requirements, the time available for thorough problem analysis and development of tailored solution methods is decreasing. There is no doubt that this trend will continue in the foreseeable future. Hence, it is not surprising that robust and general automated problem solving methods with satisfactory performance are needed. | ||
650 | 0 | _aEngineering. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aComputational intelligence. | |
650 | 1 | 4 | _aEngineering. |
650 | 2 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
700 | 1 |
_aGielen, Georges. _eauthor. |
|
700 | 1 |
_aFern�andez, Francisco V. _eauthor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783642391613 |
830 | 0 |
_aStudies in Computational Intelligence, _x1860-949X ; _v501 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-642-39162-0 |
912 | _aZDB-2-ENG | ||
942 | _cEBK | ||
999 |
_c57310 _d57310 |