2011
DOI: 10.1007/s00454-011-9344-x
|View full text |Cite
|
Sign up to set email alerts
|

Persistent Cohomology and Circular Coordinates

Abstract: Nonlinear dimensionality reduction (NLDR) algorithms such as Isomap, LLE and Laplacian Eigenmaps address the problem of representing high-dimensional nonlinear data in terms of low-dimensional coordinates which represent the intrinsic structure of the data. This paradigm incorporates the assumption that real-valued coordinates provide a rich enough class of functions to represent the data faithfully and efficiently. On the other hand, there are simple structures which challenge this assumption: the circle, for… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
166
0

Year Published

2012
2012
2022
2022

Publication Types

Select...
3
3
1

Relationship

0
7

Authors

Journals

citations
Cited by 111 publications
(166 citation statements)
references
References 13 publications
0
166
0
Order By: Relevance
“…Signals that have a hidden state space are identifiable using the topology of delay embeddings [7], a concept that can be traced to a paper by Takens [8]. Many papers have discussed ways to find the hidden state of a dynamical system; recovering the phase space from measurements [9], [10], [11], [12], [13].…”
Section: A Historical Contextmentioning
confidence: 99%
“…Signals that have a hidden state space are identifiable using the topology of delay embeddings [7], a concept that can be traced to a paper by Takens [8]. Many papers have discussed ways to find the hidden state of a dynamical system; recovering the phase space from measurements [9], [10], [11], [12], [13].…”
Section: A Historical Contextmentioning
confidence: 99%
“…Our goal in the current work is to find and visualize higher-order structures in reference traces that may extend through time, forming cycles that may be executed multiple times. de Silva et al [10] and Wang et al [28] present approaches to finding topological features, such as circles and branches, in general point sets.…”
Section: Related Workmentioning
confidence: 99%
“…With the technical tools described in [10,28], we now give an overview of our algorithm. Here we assume basic knowledge in topology and homology.…”
Section: Detecting Circular Features In a Point Cloudmentioning
confidence: 99%
See 2 more Smart Citations