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Recurrence Plot
In descriptive statistics and chaos theory, a recurrence plot (RP) is a plot showing, for each moment i in time, the times at which the state of a dynamical system returns to the previous state at i, i.e., when the phase space trajectory visits roughly the same area in the phase space as at time j. In other words, it is a plot of :\vec(i)\approx \vec(j), showing i on a horizontal axis and j on a vertical axis, where \vec is the state of the system (or its phase space trajectory). Background Natural processes can have a distinct recurrent behaviour, e.g. periodicities (as seasonal or Milankovich cycles), but also irregular cyclicities (as El Niño Southern Oscillation, heart beat intervals). Moreover, the recurrence of states, in the meaning that states are again arbitrarily close after some time of divergence, is a fundamental property of deterministic dynamical systems and is typical for nonlinear or chaotic systems (cf. Poincaré recurrence theorem). The recurrence of states i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistics
Statistics (from German: '' Statistik'', "description of a state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of surveys and experiments.Dodge, Y. (2006) ''The Oxford Dictionary of Statistical Terms'', Oxford University Press. When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey samples. Representative sampling assures that inferences and conclusions can reasonably extend from the sample to the population as a whole. An ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dot Plot (bioinformatics)
In bioinformatics a dot plot is a graphical method for comparing two biological sequences and identifying regions of close similarity after sequence alignment. It is a type of recurrence plot. History One way to visualize the similarity between two protein or nucleic acid sequences is to use a similarity matrix, known as a dot plot. These were introduced by Gibbs and McIntyre in 1970 and are two-dimensional matrices that have the sequences of the proteins being compared along the vertical and horizontal axes. For a simple visual representation of the similarity between two sequences, individual cells in the matrix can be shaded black if residues are identical, so that matching sequence segments appear as runs of diagonal lines across the matrix. Interpretation Some idea of the similarity of the two sequences can be gleaned from the number and length of matching segments shown in the matrix. Identical proteins will obviously have a diagonal line in the center of the matrix. Inse ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Self-similarity Matrix
In data analysis, the self-similarity matrix is a graphical representation of similarity measure, similar sequences in a data series. Similarity can be explained by different measures, like spatial distance (distance matrix), correlation, or comparison of local histograms or spectral properties (e.g. IXEGRAM). This technique is also applied for the search of a given pattern in a long data series as in gene matching. A similarity plot can be the starting point for Dot plot (bioinformatics), dot plots or recurrence plots. Definition To construct a self-similarity matrix, one first transforms a data series into an ordered sequence of feature vectors V = (v_1, v_2, \ldots, v_n) , where each vector v_i describes the relevant features of a data series in a given local interval. Then the self-similarity matrix is formed by computing the similarity of pairs of feature vectors : S(j,k) = s(v_j, v_k) \quad j,k \in (1,\ldots,n) where s(v_j, v_k) is a function measuring the similarity of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recurrence Quantification Analysis
Recurrence quantification analysis (RQA) is a method of nonlinear data analysis (cf. chaos theory) for the investigation of dynamical systems. It quantifies the number and duration of recurrences of a dynamical system presented by its phase space trajectory. Background The recurrence quantification analysis (RQA) was developed in order to quantify differently appearing recurrence plots (RPs), based on the small-scale structures therein. Recurrence plots are tools which visualise the recurrence behaviour of the phase space trajectory \vec(i) of dynamical systems: :(i,j) = \Theta(\varepsilon - \, \vec(i) - \vec(j)\, ), where \Theta: \mathbf \rightarrow \ is the Heaviside function and \varepsilon a predefined tolerance. Recurrence plots mostly contain single dots and lines which are parallel to the mean diagonal (''line of identity'', LOI) or which are vertical/horizontal. Lines parallel to the LOI are referred to as ''diagonal lines'' and the vertical structures as ''vertical lines ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recurrence Period Density Entropy
Recurrence period density entropy (RPDE) is a method, in the fields of dynamical systems, stochastic processes, and time series analysis, for determining the periodicity, or repetitiveness of a signal. Overview Recurrence period density entropy is useful for characterising the extent to which a time series repeats the same sequence, and is therefore similar to linear autocorrelation and time delayed mutual information, except that it measures repetitiveness in the phase space of the system, and is thus a more reliable measure based upon the dynamics of the underlying system that generated the signal. It has the advantage that it does not require the assumptions of linearity, Gaussianity or dynamical determinism. It has been successfully used to detect abnormalities in biomedical contexts such as speech signal.M. Little, P. McSharry, I. Moroz, S. Roberts (2006Nonlinear, Biophysically-Informed Speech Pathology Detectionin 2006 IEEE International Conference on Acoustics, Speech and ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Poincaré Plot
A Poincaré plot, named after Henri Poincaré, is a type of recurrence plot used to quantify self-similarity in processes, usually periodic functions. It is also known as a return map. Poincaré plots can be used to distinguish chaos from randomness by embedding a data set in a higher-dimensional state space. Given a time series of the form : x_t, x_, x_, \ldots, a return map in its simplest form first plots (''x''''t'', ''x''''t''+1), then plots (''x''''t''+1, ''x''''t''+2), then (''x''''t''+2, ''x''''t''+3), and so on. Applications in electrocardiography An electrocardiogram (ECG) is a tracing of the voltage changes in the chest generated by the heart, whose contraction in a normal person is triggered by an electrical impulse that originates in the sinoatrial node. The ECG normally consists of a series of waves, labeled the P, Q, R, S and T waves. The P wave represents depolarization of the atria, the Q-R-S series of waves depolarization of the ventricles ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Phase Synchronization
{{no footnotes, date=June 2017 Phase synchronization is the process by which two or more cyclic signals tend to oscillate with a repeating sequence of relative phase angles. Phase synchronisation is usually applied to two waveforms of the same frequency with identical phase angles with each cycle. However it can be applied if there is an integer relationship of frequency, such that the cyclic signals share a repeating sequence of phase angles over consecutive cycles. These integer relationships are called Arnold tongues which follow from bifurcation of the circle map. One example of phase synchronization of multiple oscillators can be seen in the behavior of Southeast Asian fireflies. At dusk, the flies begin to flash periodically with random phases and a gaussian distribution of native frequencies. As night falls, the flies, sensitive to one another's behavior, begin to synchronize their flashing. After some time all the fireflies within a given tree (or even larger area) wi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Matrix Product
In mathematics, particularly in linear algebra, matrix multiplication is a binary operation that produces a matrix from two matrices. For matrix multiplication, the number of columns in the first matrix must be equal to the number of rows in the second matrix. The resulting matrix, known as the matrix product, has the number of rows of the first and the number of columns of the second matrix. The product of matrices and is denoted as . Matrix multiplication was first described by the French mathematician Jacques Philippe Marie Binet in 1812, to represent the composition of linear maps that are represented by matrices. Matrix multiplication is thus a basic tool of linear algebra, and as such has numerous applications in many areas of mathematics, as well as in applied mathematics, statistics, physics, economics, and engineering. Computing matrix products is a central operation in all computational applications of linear algebra. Notation This article will use the following notat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Mutual Information
In probability theory and information theory, the mutual information (MI) of two random variables is a measure of the mutual dependence between the two variables. More specifically, it quantifies the " amount of information" (in units such as shannons (bits), nats or hartleys) obtained about one random variable by observing the other random variable. The concept of mutual information is intimately linked to that of entropy of a random variable, a fundamental notion in information theory that quantifies the expected "amount of information" held in a random variable. Not limited to real-valued random variables and linear dependence like the correlation coefficient, MI is more general and determines how different the joint distribution of the pair (X,Y) is from the product of the marginal distributions of X and Y. MI is the expected value of the pointwise mutual information (PMI). The quantity was defined and analyzed by Claude Shannon in his landmark paper "A Mathemati ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
K2 Entropy
K, or k, is the eleventh letter in the Latin alphabet, used in the modern English alphabet, the alphabets of other western European languages and others worldwide. Its name in English is ''kay'' (pronounced ), plural ''kays''. The letter K usually represents the voiceless velar plosive. History The letter K comes from the Greek letter Κ ( kappa), which was taken from the Semitic kaph, the symbol for an open hand. This, in turn, was likely adapted by Semitic tribes who had lived in Egypt from the hieroglyph for "hand" representing /ḏ/ in the Egyptian word for hand, ⟨ ḏ-r-t⟩ (likely pronounced in Old Egyptian). The Semites evidently assigned it the sound value instead, because their word for hand started with that sound. K was brought into the Latin alphabet with the name ''ka'' /kaː/ to differentiate it from C, named ''ce'' (pronounced /keː/) and Q, named ''qu'' and pronounced /kuː/. In the earliest Latin inscriptions, the letters C, K and Q were all used ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
