Fast Blind Instrument Function Estimation Method for Industrial Infrared Spectrometers

Author(s):  
Tingting Liu ◽  
Hai Liu ◽  
Zengzhao Chen ◽  
Alan M. Lesgold
1997 ◽  
Vol 13 (2) ◽  
pp. 170-184 ◽  
Author(s):  
John L. Knight ◽  
Stephen E. Satchell

This paper deals with the use of the empirical cumulant generating function to consistently estimate the parameters of a distribution from data that are independent and identically distributed (i.i.d.). The technique is particularly suited to situations where the density function is unknown or unbounded in parameter space. We prove asymptotic equivalence of our technique to that of the empirical characteristic function and outline a six-step procedure for its implementation. Extensions of the approach to non-i.i.d. situations are considered along with a discussion of suitable applications and a worked example.


2012 ◽  
Vol 271-272 ◽  
pp. 932-935
Author(s):  
Hong Ying Hu ◽  
Wen Long Li ◽  
Feng Qiang Zhao

Empirical Mode Decomposition (EMD) is a non-stationary signal processing method developed recently. It has been applied in many engineering fields. EMD has many similarities with wavelet decomposition. But EMD Decomposition has its own characteristics, especially in accurate trend extracting. Therefore the paper firstly proposes an algorithm of extracting slow-varying trend based on EMD. Then, according to wavelet regression estimation method, a new regression function estimation method based on EMD is presented. The simulation proves the advantages of the approach with easy computation and more accurate result.


2020 ◽  
Vol 11 (3) ◽  
pp. 133-150
Author(s):  
Kishore Bingi ◽  
Rosdiazli Ibrahim ◽  
Mohd Noh Karsiti ◽  
Sabo Miya Hassan ◽  
Vivekananda Rajah Harindran

Fractional-order systems and controllers have been extensively used in many control applications to achieve robust modeling and controlling performance. To implement these systems, curve fitting based integer-order transfer function estimation techniques namely Oustaloup and Matsuda are most widely used. However, these methods are failed to achieve the best approximation due to the limitation of the desired frequency range. Thus, this article presents a simple curve fitting based integer-order transfer function estimation method for fractional-order differentiator/integrator using frequency response. The advantage of this technique is that it is simple and can fit the entire desired frequency range. Using the approach, an approximation table for fractional-order differentiator has also been obtained which can be used directly to obtain the approximation of fractional-order systems. A simulation study on fractional systems shows that the proposed approach produced better parameter approximation for the desired frequency as compared to Oustaloup, refined Oustaloup and Matsuda techniques.


2012 ◽  
Vol 460 ◽  
pp. 189-192
Author(s):  
Hong Ying Hu ◽  
Chun Ming Kan

Empirical Mode Decomposition (EMD) is a non-stationary signal processing method developed recently. It has been applied in many engineering fields. EMD has many similarities with wavelet decomposition. But EMD Decomposition has its own characteristics, especially in accurate rend extracting. Therefore the paper firstly proposes an algorithm of extracting slow-varying trend based on EMD. Then, according to wavelet probability density function estimation method, a new density estimation method based on EMD is presented. The simulations of Gaussian single and mixture model density estimation prove the advantages of the approach with easy computation and more accurate result


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