Influence of prior knowledge on the accuracy limit of parameter estimation in single-molecule fluorescence microscopy
Influence of prior knowledge on the accuracy limit of parameter estimation in single-molecule fluorescence microscopy
In estimation theory, it is known that prior knowledge of parameters can improve the Cramér-Rao lower bound (CRLB). In this paper, we study the influence of prior knowledge on the CRLB of the estimates of the parameters that describe the trajectory of a moving object (single molecule). Since the CRLB is obtained from the inverse of the Fisher information matrix, we present a general expression of the Fisher information matrix in terms of the image function, the object trajectory and the prior knowledge matrix. Applying this expression to an object moving linearly in a two-dimensional (2D) plane with two distinct cases of prior knowledge, explicit CRLB expressions are derived. From these expressions, we show that the improvement in the CRLB of the parameter estimates is dependent on which parameters are known.
1304-1307
Lin, Zhiping
9b046adc-5fd0-4f26-a722-4e72598ecd9f
Wong, Yau
36160933-9ffd-441e-84f7-23ace7af822a
Ober, Raimund J.
31f4d47f-fb49-44f5-8ff6-87fc4aff3d36
2013
Lin, Zhiping
9b046adc-5fd0-4f26-a722-4e72598ecd9f
Wong, Yau
36160933-9ffd-441e-84f7-23ace7af822a
Ober, Raimund J.
31f4d47f-fb49-44f5-8ff6-87fc4aff3d36
Lin, Zhiping, Wong, Yau and Ober, Raimund J.
(2013)
Influence of prior knowledge on the accuracy limit of parameter estimation in single-molecule fluorescence microscopy.
In 2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013.
IEEE.
.
(doi:10.1109/ISCAS.2013.6572093).
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Conference or Workshop Item
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Abstract
In estimation theory, it is known that prior knowledge of parameters can improve the Cramér-Rao lower bound (CRLB). In this paper, we study the influence of prior knowledge on the CRLB of the estimates of the parameters that describe the trajectory of a moving object (single molecule). Since the CRLB is obtained from the inverse of the Fisher information matrix, we present a general expression of the Fisher information matrix in terms of the image function, the object trajectory and the prior knowledge matrix. Applying this expression to an object moving linearly in a two-dimensional (2D) plane with two distinct cases of prior knowledge, explicit CRLB expressions are derived. From these expressions, we show that the improvement in the CRLB of the parameter estimates is dependent on which parameters are known.
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Published date: 2013
Venue - Dates:
2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013, , Beijing, China, 2013-05-19 - 2013-05-23
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Local EPrints ID: 423646
URI: http://eprints.soton.ac.uk/id/eprint/423646
PURE UUID: 2b79088a-5ac7-4bdc-ac5c-55c2ad049b82
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Date deposited: 27 Sep 2018 16:30
Last modified: 16 Mar 2024 04:37
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Author:
Zhiping Lin
Author:
Yau Wong
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