Classification of Lie-like and other translation-invariant function algebras

1986 ◽  
Vol 40 (5) ◽  
pp. 866-872
Author(s):  
G. K. Tolokonnikov
Keyword(s):  
Invariant Function ◽  
Translation Invariant ◽  
Function Algebras

scholarly journals Translation Invariant Spaces and Asymptotic Properties of Variational Equations

2011 ◽  
Vol 2011 ◽  
pp. 1-36 ◽  
Author(s):  
Adina Luminiţa Sasu ◽  
Bogdan Sasu
Keyword(s):  
Control Systems ◽  
Asymptotic Properties ◽  
Sufficient Conditions ◽  
Invariant Function ◽  
Function Spaces ◽  
Skew Product ◽  
Translation Invariant ◽  
Variational Equations ◽  
Skew Product Flows ◽  
New Perspective

We present a new perspective concerning the study of the asymptotic behavior of variational equations by employing function spaces techniques. We give a complete description of the dichotomous behaviors of the most general case of skew-product flows, without any assumption concerning the flow, the cocycle or the splitting of the state space, our study being based only on the solvability of some associated control systems between certain function spaces. The main results do not only point out new necessary and sufficient conditions for the existence of uniform and exponential dichotomy of skew-product flows, but also provide a clear chart of the connections between the classes of translation invariant function spaces that play the role of the input or output classes with respect to certain control systems. Finally, we emphasize the significance of each underlying hypothesis by illustrative examples and present several interesting applications.

scholarly journals Stamps Detection and Classification Using Simple Features Ensemble

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Paweł Forczmański ◽  
Andrzej Markiewicz
Keyword(s):  
Color Space ◽  
Shape Descriptors ◽  
Translation Invariant ◽  
Space Transformation ◽  
Rubber Stamp ◽  
Color Space Transformation ◽  
Extraction Stage ◽  
Simple Features ◽  
Scanned Documents

The paper addresses a problem of detection and classification of rubber stamp instances in scanned documents. A variety of methods from the field of image processing, pattern recognition, and some heuristic are utilized. Presented method works on typical stamps of different colors and shapes. For color images, color space transformation is applied in order to find potential color stamps. Monochrome stamps are detected through shape specific algorithms. Following feature extraction stage, identified candidates are subjected to classification task using a set of shape descriptors. Selected elementary properties form an ensemble of features which is rotation, scale, and translation invariant; hence this approach is document size and orientation independent. We perform two-tier classification in order to discriminate between stamps and no-stamps and then classify stamps in terms of their shape. The experiments carried out on a considerable set of real documents gathered from the Internet showed high potential of the proposed method.

A Scale and Translation Invariant Approach for Early Classification of Spatio-Temporal Patterns Using Spiking Neural Networks

2015 ◽  
Vol 43 (2) ◽  
pp. 327-343 ◽  
Author(s):  
Banafsheh Rekabdar ◽  
Monica Nicolescu ◽  
Mircea Nicolescu ◽  
Mohammad Taghi Saffar ◽  
Richard Kelley
Keyword(s):  
Neural Networks ◽  
Temporal Patterns ◽  
Spiking Neural Networks ◽  
Translation Invariant ◽  
Early Classification ◽  
Spatio Temporal ◽  
Invariant Approach
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