Signal Extraction from Noise and Calibration

2021 ◽  
Author(s):  
Elia Stefano Battistelli
Keyword(s):  
Signal Extraction

A new method of fluxgate signal extraction

2017 ◽  
Vol 2017 (45) ◽  
pp. 83-89
Author(s):  
A.A. Marusenkov ◽  
Keyword(s):  
High Frequency ◽  
Second Harmonic ◽  
Excitation Frequency ◽  
Low Noise ◽  
Measuring System ◽  
Signal Extraction ◽  
Fluxgate Magnetometer ◽  
New Approach ◽  
Average Value ◽  
The Time Domain

Using dedicated high-frequency measuring system the distribution of the Barkhausen jumps intensity along a reversal magnetization cycle was investigated for low noise fluxgate sensors of various core shapes. It is shown that Barkhausen (reversal magnetization) noise intensity is strongly inhomogeneous during an excitation cycle. In the traditional second harmonic fluxgate magnetometers the signals are extracted in the frequency domain, as a result, some average value of reversal magnetization noises is contributed to the output signals. In order to fit better the noise shape and minimize its transfer to the magnetometer output the new approach for demodulating signals of these sensors is proposed. The new demodulating method is based on information extraction in the time domain taking into account the statistical properties of cyclic reversal magnetization noises. This approach yields considerable reduction of the fluxgate magnetometer noise in comparison with demodulation of the signal filtered at the second harmonic of the excitation frequency.

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.

Central Bank Liquidity Management and the Signal Extraction Problem on the Money Market / Die Liquiditätssteuerung der Notenbank und das Signal-extraktionsproblem am Geldmarkt

2000 ◽  
Vol 220 (3) ◽  
pp. 284-301
Author(s):  
Ulrich Bindseil
Keyword(s):  
Monetary Policy ◽  
Central Bank ◽  
Interest Rates ◽  
Term Structure ◽  
Management Strategies ◽  
Money Market ◽  
Signal Extraction ◽  
Maintenance Period ◽  
Liquidity Management ◽  
Expectation Theory

Summary Understanding the factors determining overnight rates is crucial both for central bankers and private market participants, since, assuming the validity of the expectation theory of the term structure of interest rates, expectations with regard to this “monadic” maturity should determine longer term rates, which are deemed to be relevant for the transmission of monetary policy. The note proposes a simple model of the money market within a two-day long reserve maintenance period to derive relationships between the relevant quantities, expectations concerning these quantities for the rest of the reserve maintenance period, and overnight rates. It is argued that a signal extraction problem faced by banks when observing quantities such as their aggregate reserve holdings and allotment amounts of monetary policy operations is at the core of these relationships. The usefulness of the model is illustrated by applying it to the analysis of three alternative liquidity management strategies of a central bank.

Nonlinear error signal extraction technique for real-time digital automatic control of optical interferometers

1995 ◽  
Author(s):  
Fabrizio Barone ◽  
Enrico Calloni ◽  
Luciano DiFiore ◽  
Aniello Grado ◽  
Leopoldo Milano ◽  
...  
Keyword(s):  
Automatic Control ◽  
Real Time ◽  
Signal Extraction ◽  
Extraction Technique ◽  
Error Signal ◽  
Nonlinear Error ◽  
Optical Interferometers
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