An efficient algorithm for Gaussian-based signal decomposition

Author(s):  
Zou Hong ◽  
Bao Zheng
Author(s):  
P.J. Phillips ◽  
J. Huang ◽  
S. M. Dunn

In this paper we present an efficient algorithm for automatically finding the correspondence between pairs of stereo micrographs, the key step in forming a stereo image. The computation burden in this problem is solving for the optimal mapping and transformation between the two micrographs. In this paper, we present a sieve algorithm for efficiently estimating the transformation and correspondence.In a sieve algorithm, a sequence of stages gradually reduce the number of transformations and correspondences that need to be examined, i.e., the analogy of sieving through the set of mappings with gradually finer meshes until the answer is found. The set of sieves is derived from an image model, here a planar graph that encodes the spatial organization of the features. In the sieve algorithm, the graph represents the spatial arrangement of objects in the image. The algorithm for finding the correspondence restricts its attention to the graph, with the correspondence being found by a combination of graph matchings, point set matching and geometric invariants.


2000 ◽  
Vol 39 (02) ◽  
pp. 200-203
Author(s):  
H. Mizuta ◽  
K. Yana

Abstract:This paper proposes a method for decomposing heart rate fluctuations into background, respiratory and blood pressure oriented fluctuations. A signal cancellation scheme using the adaptive RLS algorithm has been introduced for canceling respiration and blood pressure oriented changes in the heart rate fluctuations. The computer simulation confirmed the validity of the proposed method. Then, heart rate fluctuations, instantaneous lung volume and blood pressure changes are simultaneously recorded from eight normal subjects aged 20-24 years. It was shown that after signal decomposition, the power spectrum of the heart rate showed a consistent monotonic 1/fa type pattern. The proposed method enables a clear interpretation of heart rate spectrum removing uncertain large individual variations due to the respiration and blood pressure change.


2016 ◽  
Vol 2016 (7) ◽  
pp. 1-6
Author(s):  
Sergey Makov ◽  
Vladimir Frantc ◽  
Viacheslav Voronin ◽  
Igor Shrayfel ◽  
Vadim Dubovskov ◽  
...  

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