PROPHID: a data-driven multi-processor architecture for high-performance DSP

2002 ◽  
Author(s):  
J.A.J. Leijten ◽  
J.L. van Meerbergen ◽  
A.H. Timmer ◽  
J.A.G. Jess
Keyword(s):  
High Performance ◽  
Data Driven ◽  
Processor Architecture

scholarly journals Data-Driven Intelligent 3D Surface Measurement in Smart Manufacturing: Review and Outlook

Machines ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 13
Author(s):  
Yuhang Yang ◽  
Zhiqiao Dong ◽  
Yuquan Meng ◽  
Chenhui Shao
Keyword(s):  
High Resolution ◽  
High Performance ◽  
Sampling Design ◽  
Three Dimensional ◽  
Measurement Data ◽  
Data Driven ◽  
Surface Measurement ◽  
Smart Manufacturing ◽  
Future Research ◽  
3D Surface

High-fidelity characterization and effective monitoring of spatial and spatiotemporal processes are crucial for high-performance quality control of many manufacturing processes and systems in the era of smart manufacturing. Although the recent development in measurement technologies has made it possible to acquire high-resolution three-dimensional (3D) surface measurement data, it is generally expensive and time-consuming to use such technologies in real-world production settings. Data-driven approaches that stem from statistics and machine learning can potentially enable intelligent, cost-effective surface measurement and thus allow manufacturers to use high-resolution surface data for better decision-making without introducing substantial production cost induced by data acquisition. Among these methods, spatial and spatiotemporal interpolation techniques can draw inferences about unmeasured locations on a surface using the measurement of other locations, thus decreasing the measurement cost and time. However, interpolation methods are very sensitive to the availability of measurement data, and their performances largely depend on the measurement scheme or the sampling design, i.e., how to allocate measurement efforts. As such, sampling design is considered to be another important field that enables intelligent surface measurement. This paper reviews and summarizes the state-of-the-art research in interpolation and sampling design for surface measurement in varied manufacturing applications. Research gaps and future research directions are also identified and can serve as a fundamental guideline to industrial practitioners and researchers for future studies in these areas.

Optimal Data-Driven Modeling-Free Differential-Inversion-Based Iterative Control: A Wafer Stage Example

2020 ◽  
Author(s):  
Zezhou Zhang ◽  
Qingze Zou
Keyword(s):  
System Dynamics ◽  
High Performance ◽  
Random Noise ◽  
High Accuracy ◽  
Data Driven ◽  
Modeling Process ◽  
Random Disturbances ◽  
Noise Disturbances ◽  
Data Driven Modeling ◽  
Iterative Control

Abstract In this paper, an optimal data-driven modeling-free differential-inversion-based iterative control (OMFDIIC) method is proposed for both high performance and robustness in the presence of random disturbances. Achieving high accuracy and fast convergence is challenging as the system dynamics behaviors vary due to the external uncertainties and the system bandwidth is limited. The aim of the proposed method is to compensate for the dynamics effect without modeling process and achieve both high accuracy and robust convergence, by extending the existed modeling-free differential-inversion-based iterative control (MFDIIC) method through a frequency- and iteration-dependent gain. The convergence of the OMFDIIC method is analyzed with random noise/disturbances considered. The developed method is applied to a wafer stage, and shows a significant improvement in the performance.

Machine learning for high performance organic solar cells: current scenario and future prospects

2021 ◽  
Author(s):  
Asif Mahmood ◽  
Jin-Liang Wang
Keyword(s):  
Machine Learning ◽  
Solar Cell ◽  
Organic Solar Cells ◽  
Organic Solar Cell ◽  
High Performance ◽  
Material Design ◽  
Data Driven ◽  
Future Prospects ◽  
Current Scenario ◽  
Review Current

In this review, current research status about the machine learning use in organic solar cell research is reviewed. We have discussed the challenges in anticipating the data driven material design.

scholarly journals On-sky results for adaptive optics control with data-driven models on low-order modes

2020 ◽  
Vol 498 (3) ◽  
pp. 3228-3240
Author(s):  
Baptiste Sinquin ◽  
Léonard Prengère ◽  
Caroline Kulcsár ◽  
Henri-François Raynaud ◽  
Eric Gendron ◽  
...  
Keyword(s):  
Adaptive Optics ◽  
High Performance ◽  
Temporal Dynamics ◽  
Data Driven ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Integral Action ◽  
High Performance Systems ◽  
Performance Results ◽  
Low Order

ABSTRACT Dedicated tip–tilt loops are commonly implemented on adaptive optics (AO) systems. In addition, a number of recent high-performance systems feature tip–tilt controllers that are more efficient than the integral action controller. In this context, linear–quadratic–Gaussian (LQG) tip–tilt regulators based on stochastic models identified from AO telemetry have demonstrated their capacity to effectively compensate for the cumulated effects of atmospheric disturbance, windshake and vibrations. These tip–tilt LQG regulators can also be periodically retuned during AO operations, thus allowing to track changes in the disturbances’ temporal dynamics. This paper investigates the potential benefit of extending the number of low-order modes to be controlled using models identified from AO telemetry. The global stochastic dynamical model of a chosen number of turbulent low-order modes is identified through data-driven modelling from wavefront sensor measurements. The remaining higher modes are modelled using priors with autoregressive models of order 2. The loop is then globally controlled using the optimal LQG regulator build from all these models. Our control strategy allows for combining a dedicated tip–tilt loop with a deformable mirror that corrects for the remaining low-order modes and for the higher orders altogether, without resorting to mode decoupling. Performance results are obtained through evaluation of the Strehl ratio computed on H-band images from the scientific camera, or in replay mode using on-sky AO telemetry recorded in 2019 July on the CANARY instrument.

Proposal of data-driven processor architecture Qv-K1

2003 ◽  
Author(s):  
T. Kamigata ◽  
K. Murakami ◽  
M. Iwata ◽  
H. Terada
Keyword(s):  
Data Driven ◽  
Processor Architecture
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