[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Lu et al., 2017 - Google Patents

High-speed channel modeling with deep neural network for signal integrity analysis

Lu et al., 2017

View PDF
Document ID
2566604268509884622
Author
Lu T
Wu K
Yang Z
Sun J
Publication year
Publication venue
2017 IEEE 26th Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS)

External Links

Snippet

In this work, deep neural networks (DNNs) are trained and used to model high-speed channels for signal integrity analysis. The DNN models predict eye-diagram metrics by taking advantage of the large amount of simulation results made available in a previous …
Continue reading at research.google.com (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • G06F17/5009Computer-aided design using simulation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • G06N3/08Learning methods
    • G06N3/082Learning methods modifying the architecture, e.g. adding or deleting nodes or connections, pruning
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • G06N3/04Architectures, e.g. interconnection topology
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/12Computer systems based on biological models using genetic models
    • G06N3/126Genetic algorithms, i.e. information processing using digital simulations of the genetic system
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computer systems based on specific mathematical models
    • G06N7/005Probabilistic networks
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00Systems involving the use of models or simulators of said systems
    • G05B17/02Systems involving the use of models or simulators of said systems electric
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators

Similar Documents

Publication Publication Date Title
Aly An intelligent hybrid model of neuro Wavelet, time series and Recurrent Kalman Filter for wind speed forecasting
EP3805999A1 (en) Resource-aware automatic machine learning system
CN114503121A (en) Resource constrained neural network architecture search
CN109063820A (en) Utilize the data processing method of time-frequency combination Recognition with Recurrent Neural Network when long
CN111063398A (en) Molecular discovery method based on graph Bayesian optimization
CN108879732B (en) Transient stability evaluation method and device for power system
US12112261B2 (en) System and method for model parameter optimization
CN114118567B (en) Power service bandwidth prediction method based on double-channel converged network
CN113935489A (en) Variational quantum model TFQ-VQA based on quantum neural network and two-stage optimization method thereof
Lu et al. High-speed channel modeling with deep neural network for signal integrity analysis
CN115146580A (en) Integrated circuit path delay prediction method based on feature selection and deep learning
CN111058840A (en) Organic carbon content (TOC) evaluation method based on high-order neural network
Cheng [Retracted] Employment Data Screening and Destination Prediction of College Students Based on Deep Learning
Guo et al. A novel adaptive causal sampling method for physics-informed neural networks
CN105844334A (en) Radial basis function neural network-based temperature interpolation algorithm
Li et al. Self-evolution cascade deep learning model for high-speed receiver adaptation
KR102138227B1 (en) An apparatus for optimizing fluid dynamics analysis and a method therefor
WO2020255634A1 (en) Information processing system and information processing method
CN117236246A (en) Unit time sequence prediction method, device and medium considering multi-input conversion effect
Chen et al. Smooth controller design for non‐linear systems using multiple fixed models
CN117131979A (en) Traffic flow speed prediction method and system based on directed hypergraph and attention mechanism
CN113610665B (en) Wind power generation power prediction method based on multi-delay output echo state network
CN101567838A (en) Automatic correcting method of function chain neural network
CN110829434B (en) Method for improving expansibility of deep neural network tidal current model
Jia et al. An optimized classification algorithm by neural network ensemble based on PLS and OLS