Modelling Methodologies in Analogue Integrated Circuit Design

Contents
About the editors
1. Introduction / Gunhan Dundar and Mustafa Berke Yelten
Part I: Fundamentals of modelling methodologies
	2. Response surface modeling / Jun Tao, Xuan Zeng, and Xin Li
		2.1 Introduction
		2.2 Problem formulation
		2.3 Least-squares regression
		2.4 Feature selection
			2.4.1 Orthogonal matching pursuit
			2.4.2 L1-norm regularization
			2.4.3 Cross-validation
			2.4.4 Least angle regression
			2.4.5 Numerical experiments
		2.5 Regularization
		2.6 Bayesian model fusion
			2.6.1 Zero-mean prior distribution
			2.6.2 Nonzero-mean prior distribution
			2.6.3 Numerical experiments
		2.7 Summary
		Acknowledgments
		References
	3. Machine learning / Olcay Taner Yıldız
		3.1 Introduction
		3.2 Data
		3.3 Dimension reduction
			3.3.1 Feature selection
			3.3.2 Feature extraction
		3.4 Clustering
			3.4.1 K-Means clustering
			3.4.2 Hierarchical clustering
		3.5 Supervised learning algorithms
			3.5.1 Simplest algorithm: prior
			3.5.2 A simple but effective algorithm: nearest neighbor
			3.5.3 Parametric methods: five shades of complexity
			3.5.4 Decision trees
			3.5.5 Kernel machines
			3.5.6 Neural networks
		3.6 Performance assessment and comparison of algorithms
			3.6.1 Sensitivity analysis
			3.6.2 Resampling
			3.6.3 Comparison of algorithms
		References
	4. Data-driven and physics-based modeling / Slawomir Koziel
		4.1 Model classification
		4.2 Modeling flow
		4.3 Design of experiments
		4.4 Data-driven models
			4.4.1 Polynomial regression
			4.4.2 Radial basis function interpolation
			4.4.3 Kriging
			4.4.4 Support vector regression
			4.4.5 Neural networks
			4.4.6 Other methods
		4.5 Physics-based models
			4.5.1 Variable fidelity models
			4.5.2 Space mapping
			4.5.3 Response correction methods
			4.5.4 Feature-based modeling
		4.6 Model selection and validation
		4.7 Summary
		Acknowledgments
		References
	5. Verification of modeling: metrics and methodologies / Ahmad Tarraf and Lars Hedrich
		5.1 Overview
			5.1.1 State space and normal form
		5.2 Model validation
			5.2.1 Model validation metrics
		5.3 Semiformal model verification
		5.4 Formal model verification
			5.4.1 Equivalence checking
			5.4.2 Other formal techniques
		5.5 Formal modeling
			5.5.1 Correct by construction: (automatic) abstract model generation via hybrid automata
		5.6 Conclusion
		Acknowledgements
		References
Part II: Applications in analogue integrated circuit design
	6. An overview of modern, automated analog circuit modeling methods: similarities, strengths, and limitations / Alex Doboli and Ciro D’Agostino
		6.1 Introduction
		6.2 Symbolic analysis
			6.2.1 Fundamental symbolic methods
			6.2.2 Beyond linear filters: simplification and hierarchical symbolic expressions
			6.2.3 Tackling complexity: advanced symbolic representations and beyond linear analysis
		6.3 Circuit macromodeling
		6.4 Neural networks for circuit modeling
		6.5 Discussion and metatheory on analog circuit modeling
		6.6 Conclusions
		References
	7. On the usage of machine-learning techniques for the accurate modeling of integrated inductors for RF applications / Fabio Passos, Elisenda Roca, Rafael Castro-Lopez and Francisco V. Fernandez
		7.1 Introduction
		7.2 Integrated inductor design insight
		7.3 Surrogate modeling
			7.3.1 Modeling strategy
		7.4 Modeling application to RF design
			7.4.1 Inductor optimization
			7.4.2 Circuit design
		7.5 Conclusions
		Acknowledgment
		References
	8. Modeling of variability and reliability in analog circuits / Javier Martin-Martinez, Javier Diaz-Fortuny, Antonio Toro-Frias, Pablo Martin-Lloret, Pablo Saraza-Canflanca, Rafael Castro-Lopez, Rosana Rodriguez, Elisenda Roca, Francisco V. Fernandez, and Montserrat Nafria
		8.1 Modeling of the time-dependent variability in CMOS technologies: the PDO model
		8.2 Characterization of time zero variability and time-dependent variability in CMOS technologies
		8.3 Parameter extraction of CMOS aging compact models
			8.3.1 Description of the method
			8.3.2 Application examples
		8.4 CASE: a reliability simulation tool for analog ICs
			8.4.1 Simulator features
			8.4.2 TZV and TDV studied in a Miller operational amplifier
		8.5 Conclusions
		Acknowledgments
		References
	9. Modeling of pipeline ADC functionality and nonidealities / Enver Derun Karabeyoglu and Tufan Coskun Karalar
		9.1 Pipeline ADC
		9.2 Flash ADC
		9.3 Behavioral model of pipeline ADCs
			9.3.1 A 1.5-bit sub-ADC model
			9.3.2 Multiplier DAC
			9.3.3 A 3-bit flash ADC
		9.4 Sources of nonidealities in pipeline ADCs
			9.4.1 Op-amp nonidealities
			9.4.2 Switch nonidealities
			9.4.3 Clock jitter and skew mismatch
			9.4.4 Capacitor mismatches
			9.4.5 Current sources matching error
			9.4.6 Comparator offset
		9.5 Final model of the pipeline ADC and its performance results
		9.6 Conclusion
		Acknowledgement
		References
	10. Power systems modelling / Jindrich Svorc, Rupert Howes, Pier Cavallini, and Kemal Ozanoglu
		10.1 Introduction
		10.2 Small-signal models of DC–DC converters
			10.2.1 Motivation
			10.2.2 Assumptions
			10.2.3 Test vehicle
			10.2.4 Partitioning of the circuit
			10.2.5 Model types
			10.2.6 Basic theory for averaged – continuous-time model
			10.2.7 Duty-cycle signal model
			10.2.8 Pulse width modulator model
			10.2.9 Model of the power stage
			10.2.10 Complete switching, linear and small-signal model
			10.2.11 The small-signal open-loop transfer function
			10.2.12 Comparison of various models
			10.2.13 Other outputs of the small-signal model
			10.2.14 Switching frequency effect
			10.2.15 Comparison of the averaged and switching models
			10.2.16 Limitations of the averaged model
		10.3 Efficiency modelling
		10.4 Battery models
		10.5 Capacitance modelling
		10.6 Modelling the inductors
			10.6.1 Spice modelling
			10.6.2 Advanced modelling
			10.6.3 Saturation current effects and modelling
		10.7 Conclusion
		References
	11. A case study for MEMS modelling: efficient design and layout of 3D accelerometer by automated synthesis / Steffen Michael and Ralf Sommer
		11.1 Introduction
		11.2 Synthesis of MEMS designs and layouts – general aspects
		11.3 Working principle and sensor structure
		11.4 Technology
		11.5 Design strategy and modelling
			11.5.1 Library approach
			11.5.2 Modelling
		11.6 MEMS design and layout example
			11.6.1 xy Acceleration unit
			11.6.2 Accelerometer for z detection
			11.6.3 Layout
		Acknowledgement
		References
	12. Spintronic resistive memories: sensing schemes / Mesut Atasoyu, Mustafa Altun, and Serdar Ozoguz
		12.1 Background
			12.1.1 Physical structure of an MTJ
			12.1.2 The switching mechanism of STT-MRAM
		12.2 Sensing schemes of STT-MRAM
		12.3 Conclusion
		Acknowledgments
		References
	13. Conclusion / Mustafa Berke Yelten and Gunhan Dundar
Index