Sharif Digital Repository

We present a primal-dual predictor-corrector interior-point method for symmetric cone optimization. The proposed algorithm is based on the Nesterov-Todd search directions and a wide neighborhood, which is an even wider neighborhood than a given negative infinity neighborhood. At each iteration, the method computes two corrector directions in addition to the Ai and Zhang directions (SIAM J. Optim. 16, 400–417, 2005), in order to improve performance. Moreover, we derive the complexity bound of the wide neighborhood predictor-corrector interior-point method for symmetric cone optimization that coincides with the currently best known theoretical complexity bounds for the short step algorithm.... 

We present a primal-dual predictor-corrector interior-point method for symmetric cone optimization. The proposed algorithm is based on the Nesterov-Todd search directions and a wide neighborhood, which is an even wider neighborhood than a given negative infinity neighborhood. At each iteration, the method computes two corrector directions in addition to the Ai and Zhang directions (SIAM J. Optim. 16, 400–417, 2005), in order to improve performance. Moreover, we derive the complexity bound of the wide neighborhood predictor-corrector interior-point method for symmetric cone optimization that coincides with the currently best known theoretical complexity bounds for the short step algorithm.... 

We have recently proposed a correlated model to provide a Gaussian mixture representation of the cardiovascular signals, with promising results in identifying rhythm disturbances. The approach provides a transformation of the data into a set of integrable Gaussians distributed over time. Looking into the model from a new joint modeling perspective, it is capable of assembling a filtered estimation, and can be used to derive temporal information of the waveforms. In this paper, we present a step-by-step derivation of the joint model putting correlation assumptions together to conclude a minimal joint description for a pair of ECG-ABP signals. We then probe novel applications of this model,... 

In this paper, a novel nonlinear joint dynamical model is presented, which is based on a set of coupled ordinary differential equations of motion and a Gaussian mixture model representation of pulsatile cardiovascular (CV) signals. In the proposed framework, the joint interdependences of CV signals are incorporated by assuming a unique angular frequency that controls the limit cycle of the heart rate. Moreover, the time consequence of CV signals is controlled by the same phase parameter that results in the space dimensionality reduction. These joint equations together with linear assignments to observation are further used in the Kalman filter structure for estimation and tracking. Moreover,... 

We present generalizations of the previously published artificial models for generating abnormal cardiac rhythms to provide simulations of coupled cardiovascular (CV) signals with different beat morphologies. Using a joint dynamical formulation, we generate the normal morphologies of the cardiac cycle using a sum of Gaussian kernels, fitted to real CV recordings. The joint inter-dependencies of CV signals are introduced by assuming the same angular frequency and a phase coupling. Abnormal beats are then specified as new dynamical trajectories. An ergadic first-order Markov chain is also used for switching between normal and abnormal beat types. Probability transitions can be learned from... 

The study of electrocardiogram (ECG) waveform amplitudes, timings and patterns has been the subject of intense research, for it provides a deep insight into the diagnostic features of the heart's functionality. In some recent works, a Bayesian filtering paradigm has been proposed for denoising and compression of ECG signals. In this paper, it is shown that this framework may be effectively used for ECG beat segmentation and extraction of fiducial points. Analytic expressions for the determination of points and intervals are derived and evaluated on various real ECG signals. Simulation results show that the method can contribute to and enhance the clinical ECG beat segmentation performance. ©... 

We present a new modified wavelet transform, called the multiadaptive bionic wavelet transform (MABWT), that can be applied to ECG signals in order to remove noise from them under a wide range of variations for noise. By using the definition of bionic wavelet transform and adaptively determining both the center frequency of each scale together with the T-function, the problem of desired signal decomposition is solved. Applying a new proposed thresholding rule works successfully in denoising the ECG. Moreover by using the multiadaptation scheme, lowpass noisy interference effects on the baseline of ECG will be removed as a direct task. The method was extensively clinically tested with real... 

We have presented a new method for ECG baseline correction using the adaptive bionic wavelet transform (BWT). In fact by the means of BWT, the resolution in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by the signal instantaneous amplitude and its first-order differential. Besides by optimizing the BWT parameters parallel to modifying our previous thresholding rule, one can handle ECG baseline correction. First an estimation of the baseline wandering frequency is obtained and then the adaptation can be used only in three successive scales in which the mid-scale has the closest center frequency to the estimated frequency. Thus the... 

This paper presents an efficient algorithm based on a nonlinear dynamical model for the precise extraction of the characteristic points of electrocardiogram (ECG), which facilitates the HRV analysis. Determining the precise position of the waveforms of an ECG signal is complicated due to the varying amplitudes of its waveforms, the ambiguous and changing form of the complex and morphological variations with unknown sources of drift. A model-based approach handles these complications; therefore a method based on the usage of this concept in an extended Kalman filter structure has been developed. The fiducial points are detected using both the parameters of Gaussian-functions of the model, and... 

This paper presents efficient denoising and lossy compression schemes for electrocardiogram (ECG) signals based on a modified extended Kalman filter (EKF) structure. We have used a previously introduced two-dimensional EKF structure and modified its governing equations to be extended to a 17-dimensional case. The new EKF structure is used not only for denoising, but also for compression, since it provides estimation for each of the new 15 model parameters. Using these specific parameters, the signal is reconstructed with regard to the dynamical equations of the model. The performances of the proposed method are evaluated using standard denoising and compression efficiency measures. For... 

A fast algorithm based on the nonlinear dynamical model for the electrocardiogram (ECG) is presented for the precise extraction of the characteristic points of these signals with baseline drift. Using the adaptive bionic wavelet transform, the baseline wander is removed efficiently. In fact by the means of the bionic wavelet transform, the resolution in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by the signal instantaneous amplitude and its first-order differential, which results in a better baseline wander cancellation. At the next step the parameters of the model are chosen to have the least square error with the original ECG. Determining... 

In this paper a new ECG denoising scheme is proposed using a novel adaptive wavelet transform, named bionic wavelet transform (BWT), which had been first developed based on a model of the active auditory system. There has been some outstanding features with the BWT such as nonlinearity, high sensitivity and frequency selectivity, concentrated energy distribution and its ability to reconstruct signal via inverse transform but the most distinguishing characteristic of BWT is that its resolution in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by the signal instantaneous amplitude and its first-order differential. Besides by optimizing the BWT... 

The new dinuclear copper(II) complexes, Cu(II)M(II) (M = Mn, Co, Ni, Cu), of a phenol-based compartmental ligand, having dissimilar N(amine)2O2 and N(imine)2O2 coordination sites have been synthesized. In this system there are two different compartments, one has piperazinyl nitrogens and phenolic oxygens and the other compartment has meso-stilbenediamine nitrogens and phenolic oxygens as coordinating sites. The complexes were characterized by elemental analysis, IR and electronic spectra as well as conductivity measurements. Dinuclear complexes were prepared through the CuIIPbII precursor complex by transmetalation of the Pb(II) for the M(II) ion. The electrochemistry and catecholase-like... 

In this paper an efficient Altering procedure based on the Extended Kalman Filter (EKF) has been proposed. The method is based on a modified nonlinear dynamic model, previously introduced for the generation of synthetic ECG signals. We have suggested simple dynamics as the governing equations for the model parameters. Since we have not any observation for these new state variables, they are considered as hidden states. Quantitative evaluation of the proposed algorithm on the MIT-BIH signals shows that an average SNR improvement of 12 dB is achieved for a signal of -5 dB. The results show improved output SNRs compared to the EKF outputs in the absence of these new dynamics. © 2007 IEEE  

This paper presents a fuzzy approach for contrast enhancement, based on two multi-scale transforms, namely wavelet and contourlet transforms. Separability and nondirectionality of conventional 2D wavelet transform, makes it unsuitable for sparsely representation of curve or line shaped image objects. On the other hand, the contourlet transform is a good alternative for this purpose. In this paper, coefficient enhancement, both in wavelet and contourlet spaces, is carried out by making use of simple fuzzy rules. These rules make the enhancement procedure more understandable and flexible. With this method, the knowledge and experience of the expert from the distribution of the coefficients can... 

The development of noble-metal-free electrocatalysts with enhanced active sites is of great significance for the production of renewable energy on large scale. Ultrathin transition metal compounds (e.g., phosphides and sulfides) have unique structural features but their stability and electroactivity must still be improved for practical applications. We propose a new strategy to synthesis ultrathin sheets of Ni-Cu-Co transition metals on porous nickel and self-assemble them into yarn-shaped microspheres. Enhance catalytic activity and stability are then attained by thermochemical phosphorization without morphological modifications. We employed various analytical techniques including XRD, SEM,... 

Up to now, attempts for developing coarse-grained SnO2-based varistors which exhibit high nonlinearity property at lower voltage have become a challenge without any prominent result because of its unknown grain growth mechanism. In this study, the effect of CuO addition to SnO2-based varistors as a grain growth enhancer additive on microstructural development, grain growth kinetics, and electrical properties was investigated. The characterization of grain growth kinetics showed that CuO addition encouraged grain growth and enhanced the grains size as it could be seen in the activation energy which decreased from 594 kJ/mol to 364 kJ/mol. In the samples with a low amount of CuO, the solute... 

Detection and classification of ventricular complexes from the ECG is of considerable importance in Holter and critical care patient monitoring, being essential for the timely diagnosis of dangerous heart conditions. Accurate detection of premature ventricular contractions (PVCs) is particularly important in relation to life-threatening arrhythmias. In this paper, we introduce a model-based dynamic algorithm for tracking the ECG characteristic waveforms using an extended Kalman filter. The algorithm can work on single or multiple leads. A "polargram"--a polar representation of the signal--is introduced, which is constructed using the Bayesian estimations of the state variables. The polargram... 

In this paper, we describe a Gaussian wave-based state space to model the temporal dynamics of electrocardiogram (ECG) signals. It is shown that this model may be effectively used for generating synthetic ECGs as well as separate characteristic waves (CWs) such as the atrial and ventricular complexes. The model uses separate state variables for each CW, i.e. P, QRS and T, and hence is capable of generating individual synthetic CWs as well as realistic ECG signals. The model is therefore useful for generating arrhythmias. Simulations of sinus bradycardia, sinus tachycardia, ventricular flutter, atrial fibrillation and ventricular tachycardia are presented. In addition, discrete versions of... 

This research focused on making novel low-voltage SnO2 varistors by CuO addition on conventional high-voltage SnO2 varistors. Moreover, the withstand surge capability of samples was studied. The results showed that CuO addition enhances grain growth of SnO2 and coarse-grained SnO2 varistors with simple microstructures were acquired in 1 mol% CuO-doped sample. This coarse-grained SnO2 varistor presented a high nonlinear coefficient (23) and low leakage current density (23 µA/cm2) with low breakdown field value of 0.6 kV/cm. Despite the large grain size, the low residual voltage ratio (2.3) was obtained for this sample compared to the CuO-free sample. The decrease in grain electric resistivity...