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At least 451 records · Page 25Linked to original sources

PubMed2006

Dispersion-convolution model for simulating peaks in a flow injection system.

A dispersion-convolution model is proposed for simulating peak shapes in a single-line flow injection system. It is based on the assumption that an injected sample plug is expanded due to a "bulk" dispersion mechanism along the length coordinate, and that after traveling over a distance or a period of time, the sample zone will develop into a Gaussian-like distribution. This spatial pattern is further transformed to a temporal coordinate by a convolution process, and finally a temporal peak image is generated. The feasibility of the proposed model has been examined by experiments with various coil lengths, sample sizes and pumping rates. An empirical dispersion coefficient (D*) can be estimated by using the observed peak position, height and area (tp*, h* and At*) from a recorder. An empirical temporal shift (Phi*) can be further approximated by Phi*=D*/u2, which becomes an important parameter in the restoration of experimental peaks. Also, the dispersion coefficient can be expressed as a second-order polynomial function of the pumping rate Q, for which D*(Q)=delta0+delta1Q+delta2Q2. The optimal dispersion occurs at a pumping rate of Qopt=sqrt[delta0/delta2]. This explains the interesting "Nike-swoosh" relationship between the peak height and pumping rate. The excellent coherence of theoretical and experimental peak shapes confirms that the temporal distortion effect is the dominating reason to explain the peak asymmetry in flow injection analysis.

Algorithms↗

PubMed2004

Responses of central auditory neurons modeled with finite impulse response (FIR) neural networks.

To simulate central auditory responses to complex sounds, a computational model was implemented. It consists of a multi-scale classification process, and an artificial neural network composed of two modules of finite impulse response (FIR) neural networks connected to a maximum network. Electrical activities of single auditory neurons were recorded at the rat midbrain in response to a repetitive pseudo-random frequency modulated (FM) sound. The multi-scale classification process divides the training dataset into either strong or weak response using a multiple-scale Gaussian filter that based on response probability. Two modules of FIR neural network are then independently trained to model the two types of responses. This caters for the possible differences in neuronal circuitry and transmission delay. Their outputs are connected to a maximum network to generate the final output. After training, we use a different set of FM responses collected from the same neuron to test the performance of the model. Two criteria are adopted for assessment. One measures the matching of the modeled output to the actual output on a point-to-point basis. Another measures the matching of bulk responses between the two. Results show that the proposed model predicts the responses of central auditory neurons satisfactorily.

Action Potentials↗

PubMed2006

On stochastic models of dynamic disorder.

In this paper we investigate some general aspects of stochastic models of dynamic disorder. First, we reexamine the Zwanzig model for the kinetics of escape through a fluctuating hole. We show that this model is trivially connected to the canonical model of the broadening of the zero-phonon line (ZPL) in crystals. This provides a new perspective of the Wang-Wolynes expression for the rate of escape from a geometric bottleneck with non-Markovian Gaussian fluctuations. Motivated by recent single-molecule experiments, we examine more general examples of fluctuation processes from the perspective of cumulant expansions. Finally, we discuss recent single-molecule experiments probing enzyme turnover performed by Xie and co-workers.

Enzymes↗

PubMed2004

Kalman filtration of radiation monitoring data from atmospheric dispersion of radioactive materials.

A Kalman filter method using off-site radiation monitoring data is proposed as a tool for on-line estimation of the source term for short-range atmospheric dispersion of radioactive materials. The method is based on the Gaussian plume model, in which the plume parameters including the source term exhibit a 'random walk' process. The embedded parameters of the Kalman filter are determined through maximum-likelihood estimation making the filter essentially free of external parameters. The method is tested using both real and simulated radiation monitoring data. For simulated data, the method is shown to retrieve the embedded parameters employed in generating the data and to reconstruct the plume model parameters, including the source term. When tested against experimental radiation monitoring data the method is found accurately to uncover the known source term.

Air Movements↗

PubMed2002

N-dimensional nonlinear Fokker-Planck equation with time-dependent coefficients.

An N-dimensional nonlinear Fokker-Planck equation is investigated here by considering the time dependence of the coefficients, where drift-controlled and source terms are present. We exhibit the exact solution based on the generalized Gaussian function related to the Tsallis statistics. Furthermore, we show that a rich class of diffusive processes, including normal and anomalous ones, can be obtained by changing the time dependence of the coefficients.

Journal Article↗

PubMed2005

Theory of frequency and phase synchronization in a rocked bistable stochastic system.

We investigate the role of noise in the phenomenon of stochastic synchronization of switching events in a rocked, overdamped bistable potential driven by white Gaussian noise, the archetype description of stochastic resonance. We present an approach to the stochastic counting process of noise-induced switching events: starting from the Markovian dynamics of the nonstationary, continuous particle dynamics, one finds upon contraction onto two states a non-Markovian renewal dynamics. A proper definition of an output discrete phase is given, and the time rate of change of its noise average determines the corresponding output frequency. The phenomenon of noise-assisted phase synchronization is investigated in terms of an effective, instantaneous phase diffusion. The theory is applied to rectangular-shaped rocking signals versus increasing input-noise strengths. In this case, for an appropriate choice of the parameter values, the system exhibits a noise-induced frequency locking accompanied by a very pronounced suppression of the phase diffusion of the output signal. Precise numerical simulations corroborate very favorably our analytical results. The novel theoretical findings are also compared with prior ones.

Action Potentials↗

PubMed2000

Detection of Gaussian signals in Poisson-modulated interference.

Passive broadband detection of target signals by an array of hydrophones in the presence of multiple discrete interferers is analyzed under Gaussian statistics and low signal-to-noise ratio conditions. A nonhomogeneous Poisson-modulated interference process is used to model the ensemble of possible arrival directions of the discrete interferers. Closed-form expressions are derived for the recognition differential of the passive-sonar equation in the presence of Poisson-modulated interference. The interference-compensated recognition differential differs from the classical recognition differential by an additive positive term that depend on the interference-to-noise ratio, the directionality of the Poisson-modulated interference, and the array beam pattern.

Acoustics↗

PubMed1991

Derivative-free restricted maximum likelihood estimation in animal models with a sparse matrix solver.

Estimation of (co)variance components by derivative-free REML requires repeated evaluation of the log-likelihood function of the data. Gaussian elimination of the augmented mixed model coefficient matrix is often used to evaluate the likelihood function, but it can be costly for animal models with large coefficient matrices. This study investigated the use of a direct sparse matrix solver to obtain the log-likelihood function. The sparse matrix package SPARSPAK was used to reorder the mixed model equations once and then repeatedly to solve the equations by Cholesky factorization to generate the terms required to calculate the likelihood. The animal model used for comparison contained 19 fixed levels, 470 maternal permanent environmental effects, and 1586 direct and 1586 maternal genetic effects, resulting in a coefficient matrix of order 3661 with .3% nonzero elements after including numerator relationships. Compared with estimation via Gaussian elimination of the unordered system, utilization of SPARSPAK required 605 and 240 times less central processing unit time on mainframes and personal computers, respectively. The SPARSPAK package also required less memory and provided solutions for all effects in the model.

Algorithms↗

PubMed1975

[Measurement of nuclear size in cells from embryonic mouse brain in monolayer culture using automatic image analysers].

Size analyses and size classifications were made of the nuclei of embryonal mouse brain cells in monolayer culture. Measurements were made by surface analysis, using the Quantimet (1,299 nuclei), and linear analysis, using the Digiscan (1,887 nuclei). Despite the different methods of measurement and different logarithmic classification, similar distribution curves were obtained, approaching the Gaussian normal distribution. The methodical problems of karyometry as well as the problems of statistical data processing are discussed.

Animals↗

PubMed2004

Atrial activity extraction for atrial fibrillation analysis using blind source separation.

This contribution addresses the extraction of atrial activity (AA) from real electrocardiogram (ECG) recordings of atrial fibrillation (AF). We show the appropriateness of independent component analysis (ICA) to tackle this biomedical challenge when regarded as a blind source separation (BSS) problem. ICA is a statistical tool able to reconstruct the unobservable independent sources of bioelectric activity which generate, through instantaneous linear mixing, a measurable set of signals. The three key hypothesis that make ICA applicable in the present scenario are discussed and validated: 1) AA and ventricular activity (VA) are generated by sources of independent bioelectric activity; 2) AA and VA present non-Gaussian distributions; and 3) the generation of the surface ECG potentials from the cardioelectric sources can be regarded as a narrow-band linear propagation process. To empirically endorse these claims, an ICA algorithm is applied to recordings from seven patients with persistent AF. We demonstrate that the AA source can be identified using a kurtosis-based reordering of the separated signals followed by spectral analysis of the sub-Gaussian sources. In contrast to traditional methods, the proposed BSS-based approach is able to obtain a unified AA signal by exploiting the atrial information present in every ECG lead, which results in an increased robustness with respect to electrode selection and placement.

Algorithms↗

PubMed1999

On statistical properties of whole nerve cuff recordings.

Whole nerve cuff electrodes can record an electric signal generated by the superposition of single fiber action potentials (AP's). Using a simple stochastic model for the superposition of AP's, the statistical properties of nerve cuff signals are mathematically derived in this study. Consequences of common signal processing methods like rectification and time-averaging are also explained. The nerve cuff signals are found to be approximately identically, independently distributed Gaussian signals with zero mean and varying variance. The spectral properties of the cuff signals generated by single AP shape or different AP shapes are also addressed and investigated by examining the properties of the autocorrelation functions of the nerve cuff signals. The theoretical results were found to be in accordance with computer simulations and processing of actual recorded data.

Action Potentials↗

PubMed1988

Apparent movements induced by luminance modulations: a model study.

When the receptive-field profiles of the different units in the primary visual cortex are described by a series of different functions which are given by a Gaussian distribution and its first, second, and so on, spatial derivatives, a full analysis of the input-output processing of these units (under the assumption of linearity for small signals) can be achieved for a wide variety of optical stimuli consisting of closely adjacent fields modulated independently in intensity. Once the input-output relationship for one particular unit has been obtained, it is possible to calculate in a straightforward manner the spatial representation of the stimulus pattern in a two-dimensional distribution of such units. Investigations are reported into how a stimulus pattern (a dark or bright bar between two fields modulated in illuminance) is represented in a hierarchical structure of such layers of units, each layer containing just one type of receptive-field profile from the Gaussian family of derivatives. It is shown that if a visual percept is associated with the behaviour of the extrema or zero-crossings of the representations in the first few layers of such an architecture, a complete description can be given of the experimental results obtained by Gregory and Heard in their psychophysical experiments on illusory movement perception induced by luminance intensity modulations.

Attention↗

PubMed1997

Analysis of overdispersed count data by mixtures of Poisson variables and Poisson processes.

Count data often show overdispersion compared to the Poisson distribution. Overdispersion is typically modeled by a random effect for the mean, based on the gamma distribution, leading to the negative binomial distribution for the count. This paper considers a larger family of mixture distributions, including the inverse Gaussian mixture distribution. It is demonstrated that it gives a significantly better fit for a data set on the frequency of epileptic seizures. The same approach can be used to generate counting processes from Poisson processes, where the rate or the time is random. A random rate corresponds to variation between patients, whereas a random time corresponds to variation within patients.

Anticonvulsants↗

PubMed2004

Robust denoising of electrophoresis and mass spectrometry signals with minimum description length principle.

The need for high-throughput assays in molecular biology places increasing requirements on the applied signal processing and modelling methods. In order to be able to extract useful information from the measurements, the removal of undesirable signal characteristics such as random noise is required. This can be done in a quite elegant and efficient way by the minimum description length (MDL) principle, which treats and separates 'noise' from the useful information as that part in the data that cannot be compressed. In its current form the MDL denoising method assumes the Gaussian noise model but does not require any ad hoc parameter settings. It provides a basis for high-speed automated processing systems without requiring continual user interventions to validate the results as in the conventional signal processing methods. Our analysis of the denoising problem in mass spectrometry, capillary electrophoresis genotyping, and sequencing signals suggests that the MDL denoising method produces robust and intuitively appealing results sometimes even in situations where competing approaches perform poorly.

Algorithms↗

PubMed2004

Entropy of partially polarized light and application to statistical processing techniques.

We have analyzed entropy properties of coherent and partially polarized light in an arbitrary number of spatial dimensions. We show that for Gaussian fields, the Shannon entropy is a simple function of the intensity and of the Barakat degree of polarization. In particular, we provide a probabilistic interpretation of this definition of the degree of polarization. Using information theory results, we also deduce some physical properties of partially polarized light such as additivity of the entropy and depolarization effects induced by mixing partially polarized states of light. Finally, we demonstrate that entropy measures can play an important role in segmentation and detection tasks.

Journal Article↗

PubMed1997

Quantization errors of the echoes in ultrasonic pulsed flowmeter employing time domain correlation.

The implementation of Time Domain Correlation Method for blood flow velocity estimation requires the conversion of the reflected ultrasonic signals into digital format in order that the computer can be utilized to investigate the technique. A number of quanitization errors, namely, that the A/D has a finite bit resolution, only a limited number of samples of the waveform may be taken per wavelength and correlation function only exits at discrete points, have an effect on the velocity estimate. This paper discusses the effect of errors associated with A/D conversion process on the accuracy of the velocity estimate. A computer simulation was performed to achieve this goal. A band passed white Gaussian noise segment was used to simulate the reflected ultrasonic signal. The jitters of the velocity estimates corresponding various A/D resolutions were calculated and plotted. Effects of interpolating the correlation function rather than determining the complete function were presented.

Algorithms↗

PubMed2005

Specification of the observation model for regularized image up-sampling.

Regularization is one of the most promising methods for image up-sampling, which is an ill-posed inverse problem. A key element of such a regularization approach is the observation model relating the observed lower resolution (LR) image to the desired higher resolution (HR) up-sampled image, used in the data-fidelity term of the regularization cost function. This paper presents an algorithm to determine this observation model based on a model of the physical acquisition process for the LR image, and the ideal acquisition process for the desired HR image, both from the same underlying continuous image. The method is illustrated with typical scenarios corresponding to LR and HR cameras modeled by either Gaussian or rectangular apertures. Experiments with some regularized image up-samplers demonstrate the importance of using the correct, adapted observation model as determined by our algorithm. Index Terms-Camera aperture, data fidelity, image up-sampling, interpolation, multidimensional signal processing, observation model, power spectral density (PSD), super-resolution.

Algorithms↗

PubMed1988

Kinetics of domain formation by sickle hemoglobin polymers.

We have monitored the growth of domains of sickle hemoglobin polymers by using temporally and spatially resolved light scattering and birefringence measured pseudosimultaneously on a 50-microns square area. Polymerization was induced and indefinitely maintained by photolysis of the carbonmonoxy derivative using an argon ion laser. Intensity of scattering and birefringence (measured as intensity transmitted through crossed polarizers) were measured using a silicon-intensified target vidicon interfaced to a computer. Polymer concentration, as inferred by light scattering, grew with primarily circular symmetry, with approximately 20% of the signal initially in a twofold symmetric pattern. In time the circular symmetry increased. A distinct decrease in the scattering signal developed which spread outward from the center of the domain. Birefringence lagged the scattering and initially grew in a twofold pattern, with the formation of a characteristic Maltese cross only appearing much later, and well after the scattering signal had peaked. Radial profiles of the domain scattering and birefringence were both approximately gaussian. We successfully modeled the decrease in scattering by fitting the profiles to a large gaussian from which a second smaller gaussian was subtracted. This second gaussian had the width of the birefringence gaussian. The width of the birefringence gaussian grew linearly in time, while the width of the scattering gaussian showed a notable acceleration. We conclude that domains form primarily as disordered arrays which align at later times. We explain the above observations, including the shape of the birefringence progress curves, as the result of an alignment transition which is solely due to a redistribution of monomers from short to long, and from entangled to radial, polymers. We present a theoretical justification for this process in an appendix. In a separate paper (Zhou, H. X., and F. A. Ferrone, manuscript submitted for publication) we show that the gaussian shapes and acceleration of the width naturally arise from a generalization of the double nucleation mechanism for sickle hemoglobin gelation (Ferrone, F. A., J. Hofrichter, H. Sunshine, and W. A. Eaton 1980. Biophys. J. 32:361-377; Ferrone, F. A., J. Hofrichter, and W. A. Eaton. 1985. J. Mol. Biol. 183:611-631).

Birefringence↗