Electrode position scaling in realistic laplacian computation

This note discusses the effects of the electrode position scaling on the realistic Laplacian (RL) computation. It is shown that when the RL is estimated with the help of Tikhonov regularization and the generalized cross-validation (GCV) criterion, improper electrode position scaling may influence the GCV criterion, which results in the decrease of RL precision. We identify what the proper scaling should be, and we provide a closer examination of how the GCV criterion is affected by the electrode position scaling.      

A spline Laplacian ECG estimator in a realistic geometry volume conductor

We have developed a spline-based Laplacian estimator over an arbitrarily shaped surface of a volume conductor and tested its applicability to Laplacian electrocardiogram (ECG) mapping. In the newly developed algorithm, estimation of the parameters associated with the spline Laplacian is formulated by seeking the general inverse of a transfer matrix. Only one spline-parameter needs to be determined through regularization in order to estimate the realistic geometry surface Laplacian from the body surface potentials. It has been demonstrated that the rich knowledge on regularization in the inverse problems can be directly applied to estimate the spline Laplacian ECG (LECG), such as the discrepancy principle. Computer simulations have been conducted to validate the new approach in a spherical volume conductor and test the feasibility of mapping cardiac electrical sources in a realistic geometry heart-torso model. The present results demonstrate that the realistic geometry spline LECG can be estimated conveniently from the body surface potentials, is more robust against measurement noise and has better performance than the conventional five-point local Laplacian estimator.     

Improved method for computation of potentials in a realistic headshape model

The lead field analysis (LFA) algorithm, a new computational technique for the calculation of potentials on the surface of a realistic head shaped volume conductor model based on the boundary element method and the reciprocity theorem, is presented. The new algorithm, in comparison to the standard boundary element method, offers improved computational efficiency and lower storage requirements. It also yields more accurate surface potential results in the face of varying dipole source locations for a head shape boundary element model with a given number of nodes. Additionally, the algorithm results in quasi-analytic expressions of the derivatives of the surface potential with respect to the location of the sources, allowing the use of optimization techniques with better convergence properties. A set of simulations demonstrating the increased robustness of the LFA algorithm in the face of varying dipole source parameters is also described     

A computer model of human atria with reasonable computation loadand realistic anatomical properties

Atrial fibrillation is the most frequent arrhythmia, provoking discomfort, heart failure and arterial embolisms. The aim of this work is to develop a simplified anatomical computer model of human atria for the study of atrial arrhythmias and the understanding of electrical propagation mechanisms. With the model we propose, up to 40 s of real-time propagation have been simulated on a single-processor computer. The size and the electrophysiological properties of the simulated atria are within realistic values and information about anatomy has been taken into account in a three-dimensional structure. Besides normal sinus beat, pathological phenomena such as flutter and fibrillation have been induced using a programmed stimulation protocol. One important observation in our model is that atrial arrhythmias are a combination of functional and anatomical reentries and that the geometry plays an important role. This virtual atrium can reproduce electrophysiological observations made in humans but with the advantage of showing in great detail how arrhythmias are initiated and sustained. Such details are difficult or impossible to study in humans. This model will serve us as a tool to evaluate the impact of new therapeutic strategies and to improve them.     

Analog circuits optimization based on evolutionary computation techniques

This paper presents a new design automation tool, based on a modified genetic algorithm kernel, in order to improve efficiency on the analog IC design cycle. The proposed approach combines a robust optimization with corner analysis, machine learning techniques and distributed processing capability able to deal with multi-objective and constrained optimization problems. The resulting optimization tool and the improvement in design productivity is demonstrated for the design of CMOS operational amplifiers.     

Hierarchical techniques for the development of realistic models of complex computer systems

This paper presents a case study of the development of a realistic, but analytically soluble, model of a very complex Computer system. This modeling project required the development and application of new dements of technology to support the modeling process. These included the use of a hierarchic structuring procedure to provide a fonnal control structure for the modeling process, and the use of perturbation analysis to correct known deficiencies in the faithfulness of the model representation of the actual system. Particular attention was paid to the effects of passive resources, and to contention and interference effects caused by competition for shared resources. The system actually modeled is the Advanced Logistics System of the United States Air Force Logistics Command. The computer configuration of this system includes multiple CDC Cyber 70 mainframes, a large quantity of extended core storage, and approximately 100 disk drives. The analytic model was validated against a simulation which uses the logical queue structure of the software system as its basis. Excellent agreement was obtained. The entire modeling process was completed and documented in two months by a team of six analysts.     

Predictive system shutdown and other architectural techniques forenergy efficient programmable computation

With the popularity of portable devices such as personal digital assistants and personal communicators, as well as with increasing awareness of the economic and environmental costs of power consumption by desktop computers, energy efficiency has emerged as an important issue in the design of electronic systems. While power efficient ASIC's with dedicated architectures have addressed the energy efficiency issue for niche applications such as DSP, much of the computation continues to be implemented as software running on programmable processors such as microprocessors, microcontrollers, and programmable DSP's. Not only is this true for general purpose computation on personal computers and workstations, but also for portable devices, application-specific systems etc. In fact, firmware and embedded software executing on RISC and DSP processor cores that are embedded in ASIC's has emerged as a leading implementation methodology for speech coding, modem functionality, video compression, communication protocol processing etc. This paper describes architectural techniques for energy efficient implementation of programmable computation, particularly focussing on the computation needed in portable devices where event-driven user interfaces, communication protocols, and signal processing play a dominant role. Two key approaches described here are predictive system shutdown and extended voltage scaling. Results indicate that a large reduction in power consumption can be achieved over current day solutions with little or no loss in system performance     

Novel techniques for bus power consumption reduction inrealizations of sum-of-product computation

Novel techniques for power-efficient implementation of sum of product computation are presented. The proposed techniques aim at reducing the switching activity required for the successive evaluation of the partial products, in the busses connecting the storage elements where data and coefficients are stored to the functional units. This is achieved through reordering the sequence of evaluation of the partial products. Heuristics based on the traveling salesman problem are proposed to perform the reordering for different categories of algorithms. Information related to both data (dynamic) and coefficients (static) is used to drive the reordering. Experimental results from the application of the proposed techniques on several signal-processing algorithms have proven that significant switching activity savings can be achieved     

Generalized eigensystem techniques for the inverse problem ofelectrocardiography applied to a realistic heart-torso geometry

The authors have previously proposed two novel solutions to the inverse problem of electrocardiography, the generalized eigensystem technique (GES) and the modified generalized eigensystem technique (tGES), and have compared these techniques with other numerical techniques using both homogeneous and inhomogeneous eccentric spheres model problems. In those studies the authors found their generalized eigensystem approaches generally gave superior performance over both truncated singular value decomposition (SVD) and zero-order Tikhonov regularization (TIK). Here, the authors extend the comparison to the case of a realistic heart-torso geometry. With this model, the GES and tGES approaches again provide smaller relative errors between the true potentials and the numerically derived potentials than the other methods studied. In addition, the isopotential maps recovered using GES and tGES appear to be more accurate than the maps recovered using either SVD and TIK     

Regularization Approaches to Demosaicking

Demosaicking is the process of reconstructing a full resolution color image from the sampled data acquired by a digital camera that apply a color filter array to a single sensor. In this paper, we propose a regularization approach to demosaicking, making use of some prior knowledge about natural color images, such as smoothness of each single color component and correlation between the different color channels. Initially, a quadratic strategy is considered and a general approach is reported. Then, an adaptive technique is analyzed, in order to improve the reconstruction near the edges and the discontinuities of the image. This is performed using a novel strategy that avoids computational demanding iterations. The proposed approach provides good performances and candidates itself for many applications. Moreover, since the response of the pixel sensors can be taken into account, it can handle nonideal acquisition devices.     

Optimally isotropic Laplacian operator

Laplacian operators used in the literature for digital image processing are not rotationally invariant. We examine the anisotropy of 3x3 Laplacian operators for images quantized in square pixels, and find the operator which has the minimum overall anisotropy.     

拉普拉斯加权聚类算法

 本文提出了一种用于聚类分析的加权聚类算法,通过利用拉普拉斯权,将聚类对象之间的结构信息自动转换为对象的权重.由于拉普拉斯权能够描述数据的邻域结构,从而能够更好的聚类.该加权聚类算法在性能上比经典聚类算法有较大改进,还具有对孤立点鲁棒、适合类别不平衡数据聚类、对聚类个数不敏感等优点.人工数据集以及UCI标准数据集上的实验证实了本文算法的可行性和有效性.     

Regularization in tomographic reconstruction using thresholding estimators

In tomographic medical devices such as single photon emission computed tomography or positron emission tomography cameras, image reconstruction is an unstable inverse problem, due to the presence of additive noise. A new family of regularization methods for reconstruction, based on a thresholding procedure in wavelet and wavelet packet (WP) decompositions, is studied. This approach is based on the fact that the decompositions provide a near-diagonalization of the inverse Radon transform and of prior information in medical images. A WP decomposition is adaptively chosen for the specific image to be restored. Corresponding algorithms have been developed for both two-dimensional and full three-dimensional reconstruction. These procedures are fast, noniterative, and flexible. Numerical results suggest that they outperform filtered back-projection and iterative procedures such as ordered-subset-expectation-maximization.     

基于区域分割自适应的超分辨率算法

提出一个基于区域的超分辨率算法,把一张图像分成平滑区域和非平滑区域,对每一个不同图像区域采用相应的正则化项.正则化项参数也会在迭代过程中自适应的确定.实验结果表明所提出的算法在客观和主观评测都优于传统算法.     

基于正则化处理的超分辨率重建

针对超分辨率重建的病态反问题进行研究。该文首先介绍超分辨率重建的数学模型,分析了最小二乘估计及其病态性。其次给出病态问题的正则化泛函,并提出一种自适应动态确定正则化系数的方法,主要研究了迭代算法的收敛性和参数选择等问题。实验结果验证了方法的有效性。     

Body surface Laplacian ECG mapping

A new noninvasive approach has been developed to resolve spatially distributed cardiac electrical activity by measuring the surface Laplacian of the body surface potential. Computer simulations demonstrate the ability of the Laplacian map compared with the potential map to image spatially distributed dipole sources embedded in a semi-infinite volume conductor. Body surface Laplacian mapping has been implemented in human subjects utilizing dry bipolar Laplacian electrodes and compared with potential maps obtained using the central terminal of each bipolar Laplacian electrode. The body surface Laplacian ECG distribution was found to provide better spatial resolution than the body surface potential distribution. The body surface Laplacian map appears to resolve depolarization and repolarization of different regions of the heart. Further improvements of the body surface Laplacian mapping may permit noninvasive mapping of spatially distributed intracardiac events.     

Toward realistic soft-tissue modeling in medical simulation

Most of today's medical simulation systems are based on geometric representations of anatomical structures that take no account of their physical nature. Representing physical phenomena and, more specifically, the realistic modeling of soft tissue will not only improve current medical simulation systems but will considerably enlarge the set of applications and the credibility of medical simulation, from neurosurgery planning to laparoscopic-surgery simulation. To achieve realistic tissue deformation, it is necessary to combine deformation accuracy with computer efficiency. On the one hand, biomechanics has studied complex mathematical models and produced a large amount of experimental data for accurately representing the deformation of soft tissue. On the other hand, computer graphics has proposed many algorithms for the real-time computation of deformable bodies, often at the cost of ignoring the physics principles. The author surveys existing models of deformation in medical simulation and analyze the impediments to combining computer-graphics representations with biomechanical models. In particular, the different geometric representations of deformable tissue are compared in relation to the tasks of real-time deformation, tissue cutting, and force-feedback interaction. Last, the author inspects the potential of medical simulation under the development of this key technology     

Creating realistic scenes in future multimedia systems

Multimedia environments need systems with better performance to meet the growing demands for more realism. Ultra-large-scale integration will eventually make possible the advanced, real-time graphic rendering technology that such digital imagery requires. The hardware-only architecture prototype discussed in this article presents a possible solution     

Analytical approach to changepoint detection in Laplacian noise

The paper presents an analytical method using the Bayesian inference framework for the identification of time-series discontinuities, i.e. changepoints, in impulsive Laplacian noise. Exact expressions for the posterior density of the changepoint positions and the associated Bayesian model evidence are given for DC step changes. The performance of the analytical approach is compared to that predicted by a Gaussian assumption to the noise statistics and Markov chain Monte Carlo methods     

二项分布—拉普拉斯和离散的高斯—拉普拉斯边缘检测算子的 性能

本文从空域及频域两方面对二项分布——拉普拉斯(LOB)及离散的高斯——拉普拉斯(DLOG)边缘检测算子进行了分析比较.在两种算子的尺度空间常数很大时,它们的时域和频域特性及对图象进行边缘检测的性能是基本相同的.但当尺度空间常数较小时,从它们在频域中带通特性的中心频率、3分贝带宽及截止频率处的高频衰减性能进行比较可知,LOB算子稍优于离散的LOG算子.故LOB算子可看成是LOG算子的一种离散实现.文中给出了实验结果,证明了分析结果的正确性.