Ambasana et al., 2017 - Google Patents
S-parameter and frequency identification method for ANN-based eye-height/width predictionAmbasana et al., 2017
View PDF- Document ID
- 1314773486088458059
- Author
- Ambasana N
- Anand G
- Gope D
- Mutnury B
- Publication year
- Publication venue
- IEEE Transactions on Components, Packaging and Manufacturing Technology
External Links
Snippet
Design and analysis of high-speed SerDes channels primarily deal with ensuring signal integrity (SI) for desired electrical performance. SI is predominantly judged by time domain (TD) metrics: bit error rate (BER), eye-height (EH), and eye-width (EW). With increasing bit …
- 238000000034 method 0 abstract description 32
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
- G06F17/5036—Computer-aided design using simulation for analog modelling, e.g. for circuits, spice programme, direct methods, relaxation methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5068—Physical circuit design, e.g. layout for integrated circuits or printed circuit boards
- G06F17/5081—Layout analysis, e.g. layout verification, design rule check
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
- G06F2217/78—Power analysis and optimization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B17/00—Systems involving the use of models or simulators of said systems
- G05B17/02—Systems involving the use of models or simulators of said systems electric
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F7/00—Methods or arrangements for processing data by operating upon the order or content of the data handled
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Swaminathan et al. | Demystifying machine learning for signal and power integrity problems in packaging | |
| Ambasana et al. | S-parameter and frequency identification method for ANN-based eye-height/width prediction | |
| Ambasana et al. | Eye Height/Width Prediction From $ S $-Parameters Using Learning-Based Models | |
| Kim et al. | Fast and precise high-speed channel modeling and optimization technique based on machine learning | |
| Veluswami et al. | The application of neural networks to EM-based simulation and optimization of interconnects in high-speed VLSI circuits | |
| Manfredi et al. | Uncertainty assessment of lossy and dispersive lines in SPICE-type environments | |
| Goay et al. | Eye diagram contour modeling using multilayer perceptron neural networks with adaptive sampling and feature selection | |
| Triverio et al. | A parameterized macromodeling strategy with uniform stability test | |
| CN109492326B (en) | PCB signal integrity simulation system based on cloud technology and simulation method thereof | |
| Maricau et al. | Efficient variability-aware NBTI and hot carrier circuit reliability analysis | |
| Trinchero et al. | Modeling of eye diagram height in high-speed links via support vector machine | |
| Rangel-Patiño et al. | System margining surrogate-based optimization in post-silicon validation | |
| Beyene | Application of artificial neural networks to statistical analysis and nonlinear modeling of high-speed interconnect systems | |
| Ye et al. | A comprehensive and modular stochastic modeling framework for the variability-aware assessment of signal integrity in high-speed links | |
| Spina et al. | Polynomial chaos-based macromodeling of general linear multiport systems for time-domain analysis | |
| Liu et al. | A generalized fault diagnosis method in dynamic analogue circuits | |
| Wang et al. | Variability analysis of crosstalk among differential vias using polynomial-chaos and response surface methods | |
| Lho et al. | Eye-width and eye-height estimation method based on artificial neural network (ANN) for USB 3.0 | |
| Prasad et al. | Multidimensional variability analysis of complex power distribution networks via scalable stochastic collocation approach | |
| Yildiz et al. | Variance-based iterative model order reduction of equivalent circuits for EMC analysis | |
| Garbuglia et al. | Modeling electrically long interconnects using physics-informed delayed Gaussian processes | |
| Yusuf et al. | A polymorphic polynomial chaos formulation for mixed epistemic-aleatory uncertainty quantification of RF/microwave circuits | |
| Li et al. | Self-evolution cascade deep learning model for high-speed receiver adaptation | |
| Kim et al. | An efficient high-speed channel modeling method based on optimized design-of-experiment (DoE) for artificial neural network training | |
| Chinea et al. | Signal integrity verification of multichip links using passive channel macromodels |