000			03603nam a22005175i 4500
001			978-3-319-15955-3
003			DE-He213
005			20200421112546.0
007			cr nn 008mamaa
008			150220s2015 gw | s |||| 0|eng d
020			_a9783319159553 _9978-3-319-15955-3
024	7		_a10.1007/978-3-319-15955-3 _2doi
050		4	_aTK7888.4
072		7	_aTJFC _2bicssc
072		7	_aTEC008010 _2bisacsh
082	0	4	_a621.3815 _223
100	1		_aLouren�co, Ricardo. _eauthor.
245	1	0	_aAIDA-CMK: Multi-Algorithm Optimization Kernel Applied to Analog IC Sizing _h[electronic resource] / _cby Ricardo Louren�co, Nuno Louren�co, Nuno Horta.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2015.
300			_aXI, 64 p. 35 illus., 5 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringerBriefs in Applied Sciences and Technology, _x2191-530X
505	0		_aIntroduction -- Previous works on automated analog IC sizing -- AIDA-CMK: AIDA-C with MOO framework -- Multi-objective framework implementation -- Kernel validation using CEC2009 benchmarks -- Results for analog IC design -- Conclusion and Future work.
520			_aThis work addresses the research and development of an innovative optimization kernel applied to analog integrated circuit (IC) design. Particularly, this works describes the modifications inside the AIDA Framework, an electronic design automation framework fully developed by at the Integrated Circuits Group-LX of the Instituto de Telecomunica�c�oes, Lisbon. It focusses on AIDA-CMK, by enhancing AIDA-C, which is the circuit optimizer component of AIDA, with a new multi-objective multi-constraint optimization module that constructs a base for multiple algorithm implementations. The proposed solution implements three approaches to multi-objective multi-constraint optimization, namely, an evolutionary approach with NSGAII, a swarm intelligence approach with MOPSO and stochastic hill climbing approach with MOSA. Moreover, the implemented structure allows the easy hybridization between kernels transforming the previous simple NSGAII optimization module into a more evolved and versatile module supporting multiple single and multi-kernel algorithms.The three multi-objective optimization approaches were validated with CEC2009 benchmarks to constrained multi-objective optimization and tested with real analog IC design problems. The achieved results were compared in terms of performance, using statistical results obtained from multiple independent runs. Finally, some hybrid approaches were also experimented, giving a foretaste to a wide range of opportunities to explore in future work.
650		0	_aEngineering.
650		0	_aComputer-aided engineering.
650		0	_aComputational intelligence.
650		0	_aElectronic circuits.
650	1	4	_aEngineering.
650	2	4	_aCircuits and Systems.
650	2	4	_aComputer-Aided Engineering (CAD, CAE) and Design.
650	2	4	_aComputational Intelligence.
700	1		_aLouren�co, Nuno. _eauthor.
700	1		_aHorta, Nuno. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783319159546
830		0	_aSpringerBriefs in Applied Sciences and Technology, _x2191-530X
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-319-15955-3
912			_aZDB-2-ENG
942			_cEBK
999			_c58572 _d58572