An Information Theoretic Study of a Duffing Oscillator Array Reservoir Computer

2021 ◽  
Author(s):  
Md Raf E Ul Shougat ◽  
XiaoFu Li ◽  
Tushar Mollik ◽  
Edmon Perkins
Keyword(s):  
Information Theory ◽  
Complex Dynamics ◽  
Duffing Oscillator ◽  
Temporal Data ◽  
Information Theoretic ◽  
Oscillatory Systems ◽  
Processing Ability ◽  
Information Metric ◽  
Immense Potential ◽  
Insight Into

Abstract Typically, nonlinearity is considered to be problematic and sometimes can lead to dire consequences. However, the nonlinearity in a Duffing oscillator array can enhance its ability to be used as a reservoir computer. Machine learning and artificial neural networks, inspired from the biological computing framework, have shown their immense potential, especially in real-time temporal data processing. Here, the efficacy of a Duffing oscillator array is explored as a reservoir computer by using information theory. To do this, a reservoir computer model is studied numerically, which exploits the dynamics of the array. In this system, the complex dynamics stem from the Duffing term in each of the identical oscillators. The effects of various system parameters of the array on the information processing ability is discussed from the perspective of information theory. By varying these parameters, the information metric was found to be topologically mixed. Additionally, the importance of asynchrony in the oscillator array is also discussed in terms of the information metric. Since such nonlinear oscillators are used to model many different physical systems, this research provides insight into how physical nonlinear oscillatory systems can be used for dynamic computation, without significantly modifying or controlling the underlying dynamical system. To the authors' knowledge, this is the first use of Shannon's information rate for quantifying a reservoir computer of this kind, as well as the first comparison between synchronization phenomena and the computing ability of a reservoir.

scholarly journals Area Entropy and Quantized Mass of Black Holes from Information Theory

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 858
Author(s):  
Dongshan He ◽  
Qingyu Cai
Keyword(s):  
Information Theory ◽  
Black Hole ◽  
Black Hole Entropy ◽  
Quantum Corrections ◽  
Compton Wavelength ◽  
Information Theoretic ◽  
Curved Space ◽  
Thermodynamic Entropy ◽  
Hole Area ◽  
The Relationship

In this paper, we present a derivation of the black hole area entropy with the relationship between entropy and information. The curved space of a black hole allows objects to be imaged in the same way as camera lenses. The maximal information that a black hole can gain is limited by both the Compton wavelength of the object and the diameter of the black hole. When an object falls into a black hole, its information disappears due to the no-hair theorem, and the entropy of the black hole increases correspondingly. The area entropy of a black hole can thus be obtained, which indicates that the Bekenstein–Hawking entropy is information entropy rather than thermodynamic entropy. The quantum corrections of black hole entropy are also obtained according to the limit of Compton wavelength of the captured particles, which makes the mass of a black hole naturally quantized. Our work provides an information-theoretic perspective for understanding the nature of black hole entropy.

Wounded Because of Religion: Identifying the Components of Gender-Specific Religious Persecution of Christians

2021 ◽  
Vol 38 (1) ◽  
pp. 119-141
Author(s):  
Helene Fisher ◽  
Elizabeth Lane Miller ◽  
Christof Sauer
Keyword(s):  
Central African Republic ◽  
Complex Dynamics ◽  
Holistic Approach ◽  
Christian Women ◽  
Religious Persecution ◽  
The World ◽  
Gender Specific ◽  
The Church ◽  
Insight Into

Abstract Emerging understanding of gender-specific religious persecution in some of the world’s most difficult countries for Christians offers timely insight into complex dynamics in which the church and missions have too often been unwittingly complicit due to limited visibility of the components contributing to these wounds. Fresh research into these deeply wounding global phenomena stands as both a warning and a pointer towards an avenue for effective ministrations by churches and Christian ministries that are working in the most severely affected areas of the world. Drawing on the latest trends identified by World Watch Research, outcomes of the Consultation for Christian Women under Pressure for their Faith, a contemporary case study from Central African Republic, and a biblical narrative, we will explore practical opportunities for a holistic approach to bring preparedness, healing, and restoration for communities under severe pressure for their Christian faith.

scholarly journals What’s Worth Talking About? Information Theory Reveals How Children Balance Informativeness and Ease of Production

2017 ◽  
Vol 28 (7) ◽  
pp. 954-966 ◽  
Author(s):  
Colin Bannard ◽  
Marla Rosner ◽  
Danielle Matthews
Keyword(s):  
Information Theory ◽  
Information Content ◽  
Low Frequency ◽  
Initial Experiment ◽  
Information Theoretic ◽  
Information Theoretic Measures

Of all the things a person could say in a given situation, what determines what is worth saying? Greenfield’s principle of informativeness states that right from the onset of language, humans selectively comment on whatever they find unexpected. In this article, we quantify this tendency using information-theoretic measures and report on a study in which we tested the counterintuitive prediction that children will produce words that have a low frequency given the context, because these will be most informative. Using corpora of child-directed speech, we identified adjectives that varied in how informative (i.e., unexpected) they were given the noun they modified. In an initial experiment ( N = 31) and in a replication ( N = 13), 3-year-olds heard an experimenter use these adjectives to describe pictures. The children’s task was then to describe the pictures to another person. As the information content of the experimenter’s adjective increased, so did children’s tendency to comment on the feature that adjective had encoded. Furthermore, our analyses suggest that children balance informativeness with a competing drive to ease production.

Applications of Formalized Information Theory

2015 ◽  
pp. 159-178
Keyword(s):  
Information Theory ◽  
Data Compression ◽  
Theorem Proving ◽  
Formal Analysis ◽  
Theoretic Analysis ◽  
Information Theoretic ◽  
Wide Range ◽  
Comprehensive Framework

In previous chapters, the authors provided a comprehensive framework that can be used in the formal probabilistic and information-theoretic analysis of a wide range of systems and protocols. In this chapter, they illustrate the usefulness of conducting this analysis using theorem proving by tackling a number of applications including a data compression application, the formal analysis of an anonymity-based MIX channel, and the properties of the onetime pad encryption system.

scholarly journals Modeling Dynamic Behaviors within Population

2020 ◽  
Vol 34 (10) ◽  
pp. 13736-13737
Author(s):  
Nazgol Tavabi
Keyword(s):  
Social Media ◽  
Activity Patterns ◽  
Sensor Data ◽  
Physiological Data ◽  
Temporal Data ◽  
Group Level ◽  
Human Behaviors ◽  
Doctoral Research ◽  
Similarities And Differences ◽  
Insight Into

The abundance of temporal data generated by mankind in recent years gives us the opportunity to better understand human behaviors along with the similarities and differences in groups of people. Better understanding of human behaviors could be very beneficial in choosing strategies, from group-level to society-level depending on the domain. This type of data could range from physiological data collected from sensors to activity patterns in social media. Identifying frequent behavioral patterns in sensor data could give more insight into the health of a community and provoke strategies towards improving it; By analyzing patterns of behaviors in social media, platform's attributes could be adjusted to the user's needs.This type of modeling introduces numerous challenges that varies depending on the data. The goal of my doctoral research is to introduce ways to better understand and capture human behavior by modeling individual's behaviors as time series and extracting interesting patterns within them.

scholarly journals An Information-Theoretic Analysis of Flexible Efficient Cognition for Persistent Sustainable Production

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 444
Author(s):  
Stephen Fox ◽  
Adrian Kotelba
Keyword(s):  
Information Theory ◽  
Cognitive Functioning ◽  
Cognitive Science ◽  
Production Systems ◽  
Sustainable Production ◽  
Theoretic Analysis ◽  
Brain Functioning ◽  
Information Theoretic ◽  
Brain Entropy

Amidst certainty, efficiency can improve sustainability by reducing resource consumption. However, flexibility is needed to be able to survive when uncertainty increases. Apropos, sustainable production cannot persist in the long-term without having both flexibility and efficiency. Referring to cognitive science to inform the development of production systems is well established. However, recent research in cognitive science encompassing flexibility and efficiency in brain functioning have not been considered previously. In particular, research by others that encompasses information (I), information entropy (H), relative entropy (D), transfer entropy (TE), and brain entropy. By contrast, in this paper, flexibility and efficiency for persistent sustainable production is analyzed in relation to these information theory applications in cognitive science and is quantified in terms of information. Thus, this paper is consistent with the established practice of referring to cognitive science to inform the development of production systems. However, it is novel in addressing the need to combine flexibility and efficiency for persistent sustainability in terms of cognitive functioning as modelled with information theory.

The Environment and Health: An Alternative Perspective

1998 ◽  
Vol 4 (2) ◽  
pp. 20
Author(s):  
Jennifer Lewis
Keyword(s):  
Health Policy ◽  
Theoretical Approach ◽  
Complex Dynamics ◽  
Ways Of Knowing ◽  
Environment And Health ◽  
Alternative Perspective ◽  
The World ◽  
The Relationship ◽  
Insight Into ◽  
Policy Solutions

A theoretical approach which may be used to increase understanding of the dynamics of environmental and health policy is outlined. The approach deals with conceptualisations or 'ways of knowing', and, as such, tends to raise questions for debate, rather than advance policy solutions. First, it considers ways in which people have thought about and 'known' the world around them and traces how this has been important in shaping our attitudes and values in relation to it, especially in influencing environmental and health policy. Three aspects are considered: the legacy of Enlightenment and Romantic philosophical frameworks, the significance of underlying contradictory assumptions within these frameworks, and some of the implications of this for public policy. Second, it advances a specific theoretical approach ? the dialectic ? as a means of exploring the relationship between ways of thought and providing insight into the complex dynamics of policy making. It looks briefly at the example of sewage disposal policy before arguing that a dialectic approach may be applied to a range of environmental and health policy situations.

scholarly journals Quantifying Information Content in Multispectral Remote-Sensing Images Based on Image Transforms and Geostatistical Modelling

2020 ◽  
Vol 12 (5) ◽  
pp. 880
Author(s):  
Ying Zhang ◽  
Jingxiong Zhang ◽  
Wenjing Yang
Keyword(s):  
Remote Sensing ◽  
Information Theory ◽  
Information Content ◽  
Spatial Dependence ◽  
Spectral Dependence ◽  
Systematic Research ◽  
Multispectral Images ◽  
Remote Sensing Images ◽  
Information Theoretic ◽  
Information Processes

Quantifying information content in remote-sensing images is fundamental for information-theoretic characterization of remote sensing information processes, with the images being usually information sources. Information-theoretic methods, being complementary to conventional statistical methods, enable images and their derivatives to be described and analyzed in terms of information as defined in information theory rather than data per se. However, accurately quantifying images’ information content is nontrivial, as information redundancy due to spectral and spatial dependence needs to be properly handled. There has been little systematic research on this, hampering wide applications of information theory. This paper seeks to fill this important research niche by proposing a strategy for quantifying information content in multispectral images based on information theory, geostatistics, and image transformations, by which interband spectral dependence, intraband spatial dependence, and additive noise inherent to multispectral images are effectively dealt with. Specifically, to handle spectral dependence, independent component analysis (ICA) is performed to transform a multispectral image into one with statistically independent image bands (not spectral bands of the original image). The ICA-transformed image is further normal-transformed to facilitate computation of information content based on entropy formulas for Gaussian distributions. Normal transform facilitates straightforward incorporation of spatial dependence in entropy computation for the aforementioned double-transformed image bands with inter-pixel spatial correlation modeled via variograms. Experiments were undertaken using Landsat ETM+ and TM image subsets featuring different dominant land cover types (i.e., built-up, agricultural, and hilly). The experimental results confirm that the proposed methods provide more objective estimates of information content than otherwise when spectral dependence, spatial dependence, or non-normality is not accommodated properly. The differences in information content between image subsets obtained with ETM+ and TM were found to be about 3.6 bits/pixel, indicating the former’s greater information content. The proposed methods can be adapted for information-theoretic analyses of remote sensing information processes.

scholarly journals FSMI: Fast computation of Shannon mutual information for information-theoretic mapping

2020 ◽  
Vol 39 (9) ◽  
pp. 1155-1177
Author(s):  
Zhengdong Zhang ◽  
Theia Henderson ◽  
Sertac Karaman ◽  
Vivienne Sze
Keyword(s):  
Mutual Information ◽  
Fundamental Problem ◽  
Information Theoretic ◽  
Efficient Data ◽  
3D Environments ◽  
Information Metric ◽  
Computational Difficulty ◽  
First Time ◽  
Efficient Data Structures ◽  
Novel Algorithm

Exploration tasks are embedded in many robotics applications, such as search and rescue and space exploration. Information-based exploration algorithms aim to find the most informative trajectories by maximizing an information-theoretic metric, such as the mutual information between the map and potential future measurements. Unfortunately, most existing information-based exploration algorithms are plagued by the computational difficulty of evaluating the Shannon mutual information metric. In this article, we consider the fundamental problem of evaluating Shannon mutual information between the map and a range measurement. First, we consider 2D environments. We propose a novel algorithm, called the fast Shannon mutual information (FSMI). The key insight behind the algorithm is that a certain integral can be computed analytically, leading to substantial computational savings. Second, we consider 3D environments, represented by efficient data structures, e.g., an OctoMap, such that the measurements are compressed by run-length encoding (RLE). We propose a novel algorithm, called FSMI-RLE, that efficiently evaluates the Shannon mutual information when the measurements are compressed using RLE. For both the FSMI and the FSMI-RLE, we also propose variants that make different assumptions on the sensor noise distribution for the purpose of further computational savings. We evaluate the proposed algorithms in extensive experiments. In particular, we show that the proposed algorithms outperform existing algorithms that compute Shannon mutual information as well as other algorithms that compute the Cauchy–Schwarz quadratic mutual information (CSQMI). In addition, we demonstrate the computation of Shannon mutual information on a 3D map for the first time.

scholarly journals REALISMO, STRUTTURA, INFORMAZIONE

2017 ◽  
Author(s):  
Cristian Mariani
Keyword(s):  
Information Theory ◽  
Quantum Information ◽  
Scientific Practice ◽  
Quantum Information Theory ◽  
Theoretic Approach ◽  
Information Theoretic ◽  
Standard Object ◽  
The Common ◽  
Informational Realism ◽  
Information Theoretic Approach

In recent years, many scholars (Ladyman & Ross [39]; Floridi [25]; Bynum [9]) have been discussing the possibility of an ‘informational’ realism. The common idea behind these projects is that of taking the notion of ‘information’ as the central concept of both our scientific practice and our ontology. At the same time, many experts in Quantum Information Theory (Lloyd [40]; Vedral [53]; Chiribella, D’Ariano & Perinotti [14]) have developed the idea that it is possible to ground all our physical theories by following an information-theoretic approach. In what follows, I aim at showing that it is still not at all clear what does it mean to be an ‘informational realist’. Consequently, I show the reasons why I believe is misleading to talk about informational realism as something that could actually supersede the most common forms of realism, namely the standard ‘object oriented’ and the structural ones. Finally, I suggest that the only plausible way to define informational realism, and thus, more generally, to take a realist attitudine towards Quantum Information Theory, is that of assuming an epistemic and moderate structural position.

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