Real-Time Signal Extraction with Regularized Multivariate Direct Filter Approach

2015 ◽  
Vol 35 (3) ◽  
pp. 206-216
Author(s):  
Ginters Buss
Keyword(s):  
Real Time ◽  
Signal Extraction ◽  
Time Signal ◽  
Filter Approach

Real-Time Signal Extraction: a Shift of Perspective

2021 ◽  
Vol 28 (3) ◽  
pp. 497-518
Author(s):  
Marc Wildi
Keyword(s):  
Real Time ◽  
Estimation Problem ◽  
Signal Extraction ◽  
Time Signal ◽  
Methodological Framework ◽  
Us Economy ◽  
The Us ◽  
One Step ◽  
Fundamental Shift

Real-time signal extraction (RTSE) concerns the determination of optimal asymmetric filters towards the end of a time series where ⎯otherwise desirable⎯ symmetric filters cannot be applied anymore. The attractiveness of this particular estimation problem resides in the generality of its scope. For illustrative purposes we here stress realtime monitoring of the US-economy as well as multi-step ahead forecasting. Traditionally, the estimation problem addressed by RTSE is tackled in the methodological framework of the classical maximum likelihood paradigm. We here question the adequacy of this general parametric approach. In particular, we review a statistical apparatus⎯the DFA⎯ consisting of optimization criteria, diagnostics and tests which accounts for alternative user-relevant aspects of the estimation problem. Interestingly, this customization relates to an uncertainty principle which entails a fundamental shift of perspective. As a result, RTSE emerges as an autonomous discipline with proprietary concepts and statistics. With little suggestive power we may interpret the DFA as a generalization of the traditional model-based approach to more general enquiries about the future than the classical one-step ahead inference.

Electrical Probing and Surface Imaging of Deep Sub-Micron Integrated Circuits

1999 ◽  
Author(s):  
Kenneth Krieg ◽  
Richard Qi ◽  
Douglas Thomson ◽  
Greg Bridges
Keyword(s):  
High Resolution ◽  
Integrated Circuits ◽  
Real Time ◽  
High Speed ◽  
Time Signal ◽  
Surface Imaging ◽  
Atomic Force ◽  
Submicron Structures ◽  
High Resolution Images ◽  
Capacitive Loading

Abstract A contact probing system for surface imaging and real-time signal measurement of deep sub-micron integrated circuits is discussed. The probe fits on a standard probe-station and utilizes a conductive atomic force microscope tip to rapidly measure the surface topography and acquire real-time highfrequency signals from features as small as 0.18 micron. The micromachined probe structure minimizes parasitic coupling and the probe achieves a bandwidth greater than 3 GHz, with a capacitive loading of less than 120 fF. High-resolution images of submicron structures and waveforms acquired from high-speed devices are presented.

Real-time signal processing in field programmable gate array based digital gamma-ray spectrometer

2020 ◽  
Vol 91 (10) ◽  
pp. 104707
Author(s):  
Yinyu Liu ◽  
Hao Xiong ◽  
Chunhui Dong ◽  
Chaoyang Zhao ◽  
Quanfeng Zhou ◽  
...  
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Field Programmable Gate Array ◽  
Gamma Ray ◽  
Time Signal ◽  
Gamma Ray Spectrometer ◽  
Field Programmable ◽  
Gate Array ◽  
Real Time Signal Processing

scholarly journals Circulant Singular Spectrum Analysis to Monitor the State of the Economy in Real Time

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1169
Author(s):  
Juan Bógalo ◽  
Pilar Poncela ◽  
Eva Senra
Keyword(s):  
Business Cycles ◽  
Real Time ◽  
Parametric Method ◽  
Singular Spectrum Analysis ◽  
The State ◽  
Signal Extraction ◽  
Alternative Procedure ◽  
State Of The Economy ◽  
Regular Patterns ◽  
Non Parametric

Real-time monitoring of the economy is based on activity indicators that show regular patterns such as trends, seasonality and business cycles. However, parametric and non-parametric methods for signal extraction produce revisions at the end of the sample, and the arrival of new data makes it difficult to assess the state of the economy. In this paper, we compare two signal extraction procedures: Circulant Singular Spectral Analysis, CiSSA, a non-parametric technique in which we can extract components associated with desired frequencies, and a parametric method based on ARIMA modelling. Through a set of simulations, we show that the magnitude of the revisions produced by CiSSA converges to zero quicker, and it is smaller than that of the alternative procedure.

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