Expanding the Algorithmic Information Theory Frame for Applications to Earth Observation

Cerra, Daniele; Datcu, Mihai

doi:10.3390/e15010407

Cited by 11 publications

(5 citation statements)

References 33 publications

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“…This metric is closely related to the Normalized Compression Distance [27], [28]. Using it we can assess the MAI between frequency bands, for example, and build an adjacency matrix or graph defined by a set of nodes (e.g., frequencies) and edges or links (MAI between nodes using a threshold).…”

Section: F Mutual Informationmentioning

confidence: 99%

Algorithmic Complexity of EEG for Prognosis of Neurodegeneration in Idiopathic Rapid Eye Movement Behavior Disorder (RBD)

et al. 2018

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Idiopathic rapid eye movement sleep behavior disorder (RBD) is a serious risk factor for neurodegenerative processes such as Parkinson's disease (PD). We investigate the use of EEG algorithmic complexity derived metrics for its prognosis. We analyzed resting state EEG data collected from 114 idiopathic RBD patients and 83 healthy controls in a longitudinal study forming a cohort in which several RBD patients developed PD or dementia with Lewy bodies. Multichannel data from ~ 3 min recordings was converted to spectrograms and their algorithmic complexity estimated using Lempel-Ziv-Welch compression. Complexity measures and entropy rate displayed statistically significant differences between groups. Results are compared to those using the ratio of slow to fast frequency power, which they are seen to complement by displaying increased sensitivity even when using a few EEG channels. Poor prognosis in RBD appears to be associated with decreased complexity of EEG spectrograms stemming in part from frequency power imbalances and cross-frequency amplitude algorithmic coupling. Algorithmic complexity metrics provide a robust, powerful and complementary way to quantify the dynamics of EEG signals in RBD with links to emerging theories of brain function stemming from algorithmic information theory.

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Section: F Mutual Informationmentioning

confidence: 99%

Algorithmic Complexity of EEG for Prognosis of Neurodegeneration in Idiopathic Rapid Eye Movement Behavior Disorder (RBD)

et al. 2018

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“…This section summarizes the related works on compression-based pattern recognition. The compression-based pattern recognition has the advantage that it can be applied to general-purpose data such as Twitter data [8], music [9], image analysis [10,11], malware detection [12], and bioinformatics [13]. Throughout this section, we assume that objects are represented as one-dimensional strings.…”

Section: Literature Review: Compression-based Pattern Recognitionmentioning

confidence: 99%

Editing Compression Dictionaries toward Refined Compression-Based Feature-Space

2022

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This paper investigates how to construct a feature space for compression-based pattern recognition which judges the similarity between two objects x and y through the compression ratio to compress x with y (’s dictionary). Specifically, we focus on the known framework called PRDC, which represents an object x as a compression-ratio vector (CV) that lines up the compression ratios after x is compressed with multiple different dictionaries. By representing an object x as a CV, PRDC makes it possible to apply vector-based pattern recognition techniques to the compression-based pattern recognition. For PRDC, the dimensions, i.e., the dictionaries determine the quality of the CV space. This paper presents a practical technique to modify the chosen dictionaries in order to improve the performance of pattern recognition substantially: First, in order to make the dictionaries independent from each other, our method leaves any word shared by multiple dictionaries in only one dictionary and assures that any pair of dictionaries have no common words. Next, we transfer words among the dictionaries, so that all the dictionaries may keep roughly the same number of words and acquire the descriptive power evenly. The application to real image classification shows that our method increases classification accuracy by up to 8% compared with the case without our method, which demonstrates that our approach to keep the dictionaries independent is effective.

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“…Cerra and Datcu develop a similar measure, called Normalized Relative Complexity, based on an approximation of the Kolmogorov cross-complexity, which leads to a formulation that is slightly different than the NRC proposed by Pinho and colleagues. They later extend the technique for pattern recognition [ 12 ]. Cerra et al also deal with the problem of text processing using a measure called Fast Compression Distance, that that computes the similarity between two texts using the intersection set between two dictionaries.…”

Section: Previous Workmentioning

confidence: 99%

Visual Analysis of Research Paper Collections Using Normalized Relative Compression

Vázquez

2019

Entropy

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The analysis of research paper collections is an interesting topic that can give insights on whether a research area is stalled in the same problems, or there is a great amount of novelty every year. Previous research has addressed similar tasks by the analysis of keywords or reference lists, with different degrees of human intervention. In this paper, we demonstrate how, with the use of Normalized Relative Compression, together with a set of automated data-processing tasks, we can successfully visually compare research articles and document collections. We also achieve very similar results with Normalized Conditional Compression that can be applied with a regular compressor. With our approach, we can group papers of different disciplines, analyze how a conference evolves throughout the different editions, or how the profile of a researcher changes through the time. We provide a set of tests that validate our technique, and show that it behaves better for these tasks than other techniques previously proposed.

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Expanding the Algorithmic Information Theory Frame for Applications to Earth Observation

Cited by 11 publications

References 33 publications

Algorithmic Complexity of EEG for Prognosis of Neurodegeneration in Idiopathic Rapid Eye Movement Behavior Disorder (RBD)

Algorithmic Complexity of EEG for Prognosis of Neurodegeneration in Idiopathic Rapid Eye Movement Behavior Disorder (RBD)

Editing Compression Dictionaries toward Refined Compression-Based Feature-Space

Visual Analysis of Research Paper Collections Using Normalized Relative Compression

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