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Registration for sequential images has significant meanings in clinical diagnosis and analysis. Many researches are concentrated on using higher-order mutual information (HMI) to fulfill the registration task. But HMI has some disadvantages, which limit the applications of HMI to a large degree. The paper proposes a new registration measure, called nonlinear correlation information entropy (NCIE), which is revised from mutual information (MI) and can be easily sensitive to the amount of nonlinear correlation information between multiple variables. Using this measure we conduct some simulations. The registration results testify that the registration method based on maximization of NCIE is a very useful and efficient method for sequential images registration.

For many technological networks, the network structures and the traffic taking place on them mutually interact. The demands of traffic increment spur the evolution and growth of the networks to maintain their normal and efficient functioning. In parallel, a change of the network structure leads to redistribution of the traffic. In this paper, we perform an extensive numerical and analytical study, extending results of Wang [Phys. Rev. Lett. 94, 188702 (2005)]. By introducing a general strength-coupling interaction driven by the traffic increment between any pair of vertices, our model generates networks of scale-free distributions of strength, weight, and degree. In particular, the obtained nonlinear correlation between vertex strength and degree, and the disassortative property demonstrate that the model is capable of characterizing weighted technological networks. Moreover, the generated graphs possess both dense clustering structures and an anticorrelation between vertex clustering and degree, which are widely observed in real-world networks. The corresponding theoretical predictions are well consistent with simulation results.

While much work has been done in finding linear correlation among subsets of features in high-dimensional data, work on detecting nonlinear correlation has been left largely untouched. In this paper, we present an algorithm for finding and visualizing nonlinear correlation clusters in the subspace of high-dimensional databases.Unlike the detection of linear correlation in which clusters are of unique orientations, finding nonlinear correlation clusters of varying orientations requires merging clusters of possibly very different orientations. Combined with the fact that spatial proximity must be judged based on a subset of features that are not originally known, deciding which clusters to be merged during the clustering process becomes a challenge. To avoid this problem, we propose a novel concept called co-sharing level which captures both spatial proximity and cluster orientation when judging similarity between clusters. Based on this concept, we develop an algorithm which not only detects nonlinear correlation clusters but also provides a way to visualize them. Experiments on both synthetic and real-life datasets are done to show the effectiveness of our method.

A global optimization technique for image registration using the concept of nonlinear correlation information entropy (NCIE) as the matching criterion is presented. The method makes it possible to efficiently overcome the local minima problem utilizing the extremum property of NCIE. Furthermore, the improved downhill simplex algorithm incorporated variant accuracy tolerance can reduce the evaluation times greatly as well as obtain an accurate and optimal transformation. Applying to register the magnetic resonance images of brain, the global optimization technique shows the validity and robustness in global searching range.

This paper presents a general methodology for learning articulated motions that, despite having non-linear correlations, are cyclical and have a defined pattern of behavior Using conventional algorithms to extract features from images, a Bayesian classifier is applied to cluster and classify features of the moving object. Clusters are then associated in different frames and structure learning algorithms for Bayesian networks are used to recover the structure of the motion. This framework is applied to the human gait analysis and tracking but applications include any coordinated movement such as multi-robots behavior analysis.

This paper shows that quantisation of colour pixels, essential to digital imagery, causes non-linear correlation in the permitted values of chromaticity coordinates in linear-intensity CIE colour spaces. It follows that colour video and image coding schemes based on these colour spaces will suffer an inherent preference for certain chromaticities.

A new adaptation algorithm for adaptive filters is proposed, introducing "adaptive threshold" in the nonlinear correlation function. The adaptive threshold varies according to the long-term average of the error signal plus the additive noise, which makes the adaptive filtering system highly robust against sharp increase in the noise yet maintains the fast convergence and low residual error properties. Results of simulation and theoretical calculation prove the effectiveness of the proposed algorithm and its superiority to the conventional LMS algorithm in an impulse noise environment.

The diagnostic method for medium voltage cables based on the method of discharge current is an integral measurement technique, which means that the dielectric properties of an insulating material can only be measured in general, singular vacancies cannot be detected. The nonlinear correlation between charging voltage and discharge current is a criterion for the state of ageing of the insulating material and gives information about its condition. The authors briefly discuss the determination of ageing of plastic insulated cables and the course of measures as follows: period of charge; period of self-discharge; and period of discharge.

A climate network of extreme rainfall over eastern Asia is constructed for the period of 1971?2000, employing the tools of complex networks and a measure of nonlinear correlation called event synchronization (ES). Using this network, we predict the extreme rainfall for several cases without delay and with n-day delay (1 ? n ? 10). The prediction accuracy can reach 58% without delay, 21% with 1-day delay, and 12% with n-day delay (2 ? n ? 10). The results reveal that the prediction accuracy is low in years of a weak east Asia summer monsoon (EASM) or 1 year later and high in years of a strong EASM or 1 year later. Furthermore, the prediction accuracy is higher due to the many more links that represent correlations between different grid points and a higher extreme rainfall rate during strong EASM years.

Dual nonlinear correlation (DNC) is a general operation in optical pattern recognition involving linear and nonlinear filtering methods. Computer controlled DNC processor is based on a two-step optoelectronic joint transform correlator with the power-law nonlinearities introduced in both channels. The DNC optoelectronic processor is sensitive to the value of power-law nonlinearities and can be adapted to the recognition task on various levels of discrimination capability. A CCD camera and a spatial light modulator are the two basic components of the processor that performs the DNC. Their characteristics such as saturation effect and limited number of quantization levels have strong influence on the correlation signal. In this paper we analyze the performance of the DNC processor and present some applications to textured and color pattern recognition with variable discrimination capability.© (1999) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Mathematical fundamentals of neurobiologic, equivalence algebra and equivalence models of neural networks are considered. Modified equivalence models of neural networks and associative memory for space-invariant 2D pattern recognition are proposed. They are based on the use of equivalence functions, including normalized ones, characterizing the similarity equivalence degree of two images, depending on their mutual space displacement. Relations between the equivalence functions and correlation functions are found out. Simulation results, demonstrating efficiency of the models on the example of 8.8 pixels patterns recognition with number of etalons, equaled to 4. Possible variants of the models implementations are considered. Neural networks architecture for invariant 2D pattern recognition consists of equivalentors, every of which replace two correlators.

Objective: To compare measurements of regional myocardial blood flow between color and radioactive microspheres. Design: Prospective, randomized, controlled. Setting: University research laboratory. Participants: Pigs. Interventions: Pigs underwent constriction of the left anterior descending artery, either incremental and then 0 constriction with epinephrine, 0.5 to 3 μ/kg/min (n = 5; “variable”) or only 0% and 100% constriction without epinephrine (n = 4, “single”). Radioactive and color microspheres were injected simultaneously. For variable constriction, 5 colors (3 × 106/mL) were tested in random order and, for single, red and yellow (6 × 106/2 mL). Measurements and Main Results: Measurements of regional endocardial, epicardial, and transmural myocardial blood flow were compared by regression analysis (linear and nonlinear). With radioactive measurements as the point of reference, when regional flow was 50 to 150 mL/min/100 g, correlation was high (r = 0.85), although regression slope was low. With endocardial and epicardial flow between 30 and 100 mL/min/100 g, correlation was close (r = 0.84). Overall nonlinear correlation was higher with single than variable constriction (r = 0.72). When regional flow was less than 100 mL/min/100 g, linear correlation was r = 0.72. When transmural flow measured by color microspheres was less than 25 mL/min/100 g, correlation was high (r = 0.86) but, with endocardial or epicardial flow, low (r = 0.67). When transmural flow was greater than 100 mL/min/100 g, correlation was extremely low (r = 0.1; n = 26 data points). The overall correlations for regional endocardial and epicardial flows were also low, except in the ischemic zone. Conclusions: Color and radioactive measurements correlate well during modereate and ischemic regional myocardial blood flow, ischemic blood flow requiring a higher concentration of color microspheres. A major limitation of using color microspheres is imprecision when flow is greater than 150 mL/min 100 g.

A variety of techniques have been used for quantitative estimation of renal transit time. We compared different indices of transit time in a group of 30 patients having baseline and ACE inhibitor technetium-99m mercaptoacetyltriglycine (MAG3) renography prior to arteriography: peak time, mean transit time, and the ratio of background-subtracted counts at 20 min to those at 3 min. Each index was calculated from whole-kidney ROI, cortical ROI, and cortical factor (by factor analysis). The strongest correlations between angiographic percent of stenosis and transit time index were observed for the peak time (Spearman p=0.469, n=53, P0.005) and for the R20/3 (again p=0.469, n=53, P0.005) using the whole-kidney ROI and using only the baseline data without captopril. (Spearman's p is simply the correlation coefficient calculated from rank in list, which allows for nonlinear correlation.) Thus simple indices of transit time (whole-kidney peak time and R20/3) correlated as well with the observed pathology as did more complicated methods that required deconvolution, factor analysis, or selection of a cortical ROI.

The influence of photoperiod on plasma growth hormone (GH) levels during parr smolt transformation was studied in Atlantic salmon, using a specific salmon GH radioimmunoassay; in addition, the impact of endogenous changes in GH levels on hypoosmoregulatory ability and growth was assessed using seawater challenge tests and measurements of growth rates. Groups of fish were kept on simulated natural photoperiod or continuous light, and subgroups were subjected to reciprocal transfers between these two light regimes at different times. For Atlantic salmon on simulated natural photoperiod, GH levels increased during the parr-smolt transformation, from 0.6 ng ml-1 in January-March to 6.6 ng ml-1 in June, while the corresponding change in fish on continuous light was from 0.4 to 1.0 ng ml-1. The study demonstrates that photoperiod is a major zeitgeber for the increased GH levels during the parr-smolt transformation of Atlantic salmon. The data further support the view that exposure to continuous light into fall and winter causes a "free running" of an endogenous rhythm governing smolting and a subsequent phase-delay of the parr-smolt transformation-related increase in plasma GH levels. A strong positive nonlinear correlation was found between specific growth rate and GH levels, with growth rate increasing rapidly with increasing GH levels up to 2-3 ng ml-1 at which point near maximal growth rate is reached. revealing that relatively small increases in GH levels may be of great importance for an increased specific growth rate. A positive nonlinear correlation was also found between GH and hypoosmoregulatory ability, leading to the conclusion that a regime of continuous light has adverse effects on seawater tolerance and that a period of short daylength is necessary for the normal smolt-related physiological improvement in seawater adaptability.

We present a nonlinear correlation methodology to recognize objects. This system is invariant to position, rotation, and scale by using vectorial signatures obtained from the target such as those from problem images. Vectorial signatures are calculated through several mathematical transformations such as scale and Fourier transform. In this application, vectorial signatures are compared using nonlinear correlations. Also, experiments were carried out in order to find the noise tolerance. The discrimination coefficient was used as a metric in performance evaluation in presence of noise. In addition, spectral index and vectorial signature index are obtained in order to recognize objects in a simpler way. This technique has low computational cost. The invariance to position, rotation, and scale digital system was tested with 21 different fossil diatoms images. The results obtained are good, and the confidence level is above 95.4%. © 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). (DOI

We present a two-layer neural network for processing of three-dimensional (3D) images that are obtained by digital holography. The network is trained with a real 3D object to compute the weights of the layers. Experiments are presented to illustrate the system performance. The system is designed to detect a 3D object in the presence of various distortions. As an example, experiments are presented to illustrate how the system is able to recognize a 3D object with 360 degrees out-of-plane rotation.

The authors investigate the rejection of PSK interference in a DS-SS/QPSK system using a complex adaptive filter and a nonlinear correlation receiver with soft-limiter. This system leads to a decrease in error probability for several orders of magnitude compared to the system which uses a complex adaptive filter and a linear receiver.

Basically two different methods have been used to determine simultaneously the intrinsic source parameters and the source location and/or station residuals. One is a linearized least-squares method, the other method uses a nonlinear correlation procedure. The two methods have been applied here to the same long-period (∼ 25 s) GDSN data from a set of earthquakes under the Tibetan plateau. In these circumstances it is found that the nonlinear correlation method leads to more stable and reliable results, which can be interpreted in a geophysically meaningful way. The results show that all of the events are shallow focus (⩽ 10 km) and in accordance with east-west extensional tectonics. The time delays obtained by the correlation method were used to infer S-P residuals associated with the near-source structure. Although the number of data is rather small, they do suggest a trend to high residuals in Northern Tibet (4.6 and 4.8 s relative to J-B times), corroborating earlier findings.

A nonlinear dynamical equation for the electronic collective motion is presented by employing the traditional time-dependent procedure. The equation is applied to the model π-electron system of ethylene, and the effects of nonlinear interactions are investigated using its several states as reference states. It is shown that the nonlinear correlation plays an important role in describing the change of the lower excited states.

Summary Studies which have previously examined the relationship between ego and moral development have found substantial correlations. However, they have used both child and adult Ss, thereby focusing on maturational aspects of development. Also, they have employed linear parametric correlations, which may have been inappropriate for the scaling level of the data. The present study employed only adult Ss, and a nonlinear, nonparametric measure of correlation was developed to examine the relationship between ego and moral development scores. Nonparametric analysis of the variance revealed a significant relationship between scores on the two measures and yielded a moderately high nonlinear correlation coefficient (η2 = .42).

A new nonlinear correlation method which makes it possible to measure the duration of uv ultrashort pulses has been proposed. In this method the multiphoton ionization of gases is used as a nonlinear process and the ion current caused by the process is detected. We have also experimentally demonstrated its usefulness in the uv region by observing the second- and the third-order auto-correlation profiles of picosecond pulses at 2661 A (the fourth harmonic of a mode-locked YAG laser), using NO and Xe gases, respectively.

SummaryTotal P monitor data were analysed by mathematical spectral analysis in order to obtain more information on the transient behaviour of P time series at different depths and the correlations between these adjacent sampling points. It was observed, that the monitor data prove annual oscillations as well as strong oscillations of shorter periods. There is a linear correlation between the various monitor depths during the annual cycle. The shorter cycles correlate differently. There was further evidence for the assumption, that there is a nonlinear correlation between soluble and particulate P in the same depths, both for epilimnic and hypolimnic water.

407 newborns with idiopathic transitory hyperbilirubinaemia were examined with regard to the decrease in serum bilirubin levels during 24 hours of intermittent phototherapy (12 hours of light exposure). The photoeffect (i. e. decrease of serum bilirubin concentration after 24 hours of therapy) showed a unique and predictable nonlinear correlation with the plasma bilirubin concentration before treatment. This relationship can be used for individualizing the duration of phototherapy and the dose of light. The apparent effect of birth weight, gestational age, and postnatal age on the efficiency of phototreatment is only due to differing initial levels of bilirubin concentration. Intermittent illumination seemed to be more efficient than continuous.

Semiquantitative determinations of kaolinite and chlorite by X-ray diffraction may be based on comparison of basal reflection peak intensities of untreated and HCl-treated samples (chlorite dissolves). The X-ray intensity of kaolinite is markedly influenced by this treatment, and quantitative determinations become unreliable. The intensity ratio of the two minerals may be obtained from “slow scan records” of the twin peak of kaolinite (002) and chlorite (004) at 3.58 A and 3.54 A, respectively. Interference between the closely spaced reflections produces a nonlinear correlation between weight and intensities, but acceptable results are obtained by calibrating the twin peak at 3.5 A, using mixtures of kaolinite and chlorite of known composition with X-ray intensity patterns similar to the minerals in the samples investigated.

The solubility of hydrogen was measured in solid Ni, Co, and Cu, and in the Ni−Co and Ni−Cu systems. A unique sampling technique was used in which equilibrated specimens were quenched by dropping into mercury. The measurements were made as a function of temperature in the range from 700° to 1225°C and of hydrogen pressure, up to 1 atm. Dissolved hydrogen in all metals and alloys obeyed Sieverts' Law. An attempt was made to correlate the hydrogen solubility with solution models based on the electronic structure of the alloys. A nonlinear correlation was found with the electronic specific heat coefficient which relates to the density of states at the Fermi surface.

Relationships between the growth efficiencies and assimilation efficiency of an animal are presented, using energy budgets compiled from the literature. Net growth efficiency is negatively correlated with assimilation efficiency and may range from 20% to 90%. Gross growth efficiencies normally fluctuate between 15% and 35% and demonstrate a nonlinear correlation with assimilation efficiency. Carnivores tend to have high assimilation efficiencies and low net growth efficiencies; herbivore/detritivores have lower assimilation efficiencies and higher net growth efficiencies. Implications of the relationships are discussed.

Different methods for calculating the renal clearance of 131I-hippuric acid with the single injection technique are evaluated. A previous procedure assumed a two-compartment model for the distribution of 131I-hippuric acid, and the renal clearance was determined from the externally measured blood curve and two blood samples. The authors have simplified this system by using a single-compartment approximation for the distribution of 131I-hippuric acid. The values calculated from the single-compartment model were shown to be too high. However, a nonlinear correlation was shown to exist between these values and the values obtained with the two-compartment model, and the clearance may be calculated from a correlation curve or a formula. The one blood sample procedure has been used in conjunction with isotope renography.

A nonlinear correlation has been found between the 29Si-15N spin-spin coupling constants and the 15N-NMR chemical shifts in silatranes. The dependence has been used to calculate corrections to the spin-spin coupling constant for the electronegativity of a substituent on the silicon atom. This has allowed the previously obtained data on the length and order of the N → Si coordinate bond for silatranes in solutions to be refined.

The results of two procedures for measuring the loudness level of tinnitus will be presented. The traditional procedure yielded significantly smaller loudness matches, when expressed in decibel sensation level (i.e., dB SL), than did the Goodwin procedure. The Goodwin procedure is more sensitive to pharmacologically induced changes in tinnitus loudness than is the traditional procedure. The Goodwin method correlates well with changes in patients subjective rating of tinnitus severity. The Goodwin match has a larger reliability coefficient. Nonlinear correlation also indicates that the Goodwin procedure is superior to the traditional method.

The integration of photon-counting imaging techniques and optical encryption systems can improve information authentication robustness against intruder attacks. Photon-counting imaging generates distributions with far fewer photons than conventional imaging and provides substantial bandwidth reduction by generating sparse encrypted data. We show that photon-limited encrypted distributions have sufficient information for successful decryption, authentication and signal retrieval. Additional compression of the encrypted distribution is applied by limiting the number of phase values used to reproduce the phase information of the complex-valued encrypted data. The validity of this technique—with and without phase compression—is probed through simulated experiments for two types of input images: alphanumerical signs and dithered natural scenes.

The globally growing market for polymer composites and their increasing use within aircraft structures has necessitated reliable bonding of composite laminates to prevent structural failure. However, knowledge behind the interaction between curing process parameters and the failure of polymer composite bonded joints is not keeping pace with the market. A novel nonlinear correlation analysis has been employed and applied to experimental data, to attentively quantify the effect of curing parameters on the failure of bonded composite assemblies. The materials (adherends and adhesive) and the bonding processes were selected from those used in assembly of composite aircraft structures.

Mechanochemical methods offer unprecedented academic and industrial opportunities for solvent-free synthesis of novel materials. The need to study mechanochemical mechanisms is growing, and has led to the development of real-time in situ X-ray powder diffraction techniques (RI-XRPD). However, despite the power of RI-XRPD methods, there remain immense challenges. In the present contribution, many of these challenges are highlighted, and their effect on the interpretation of RI-XRPD data considered. A novel data processing technique is introduced for RI-XRPD, through which the solvent-free mechanochemical synthesis of an organic salt is followed as a case study. These are compared to ex situ studies, where notable differences are observed. The process is monitored over a range of milling frequencies, and a nonlinear correlation between milling parameters and reaction rate is observed. Kinetic analysis of RI-XRPD allows, for the first time, observation of a mechanistic shift over the course of mechanical treatment, resulting from time evolving conditions within the mechanoreactor.