JPEG2000-coded image error concealment exploiting convex sets projections.

Transmission errors in JPEG2000 can be grouped into three main classes, depending on the affected area: LL, high frequencies at the lower decomposition levels, and high frequencies at the higher decomposition levels. The first type of errors are the most annoying but can be concealed exploiting the signal spatial correlation like in a number of techniques proposed in the past; the second are less annoying but more difficult to address; the latter are often imperceptible. In this paper, we address the problem of concealing the second class or errors when high bit-planes are damaged by proposing a new approach based on the theory of projections onto convex sets. Accordingly, the error effects are masked by iteratively applying two procedures: low-pass (LP) filtering in the spatial domain and restoration of the uncorrupted wavelet coefficients in the transform domain. It has been observed that a uniform LP filtering brought to some undesired side effects that negatively compensated the advantages. This problem has been overcome by applying an adaptive solution, which exploits an edge map to choose the optimal filter mask size. Simulation results demonstrated the efficiency of the proposed approach.     

Fast detection and characterization of vessels in very large 3-D data sets using geometrical moments

An improved and very fast algorithm dealing with the extraction of vessels in three-dimensional imaging is described. The approach is based on geometrical moments and a local cylindrical approximation. A robust estimation of vessel and background intensity levels, position, orientation, and diameter of the vessels with adaptive control of key parameters, is provided during vessel tracking. Experimental results are presented for lower limb arteries in multidetector computed tomography scanner.     

Fast all-optical flip-flop memory exploiting the electric field nonlinearity of coherent laser amplifiers

The coherent nonlinear feedback in an integrated optical flip-flop is studied in order to demonstrate device applications of laser amplifiers operated above the laser threshold. The nonlinear feedback is provided by the stabilizing fields of the laser amplifiers, interfering with coherent optical reference fields. In both stable states of the flip-flop, the nonlinear feedback allows the laser amplifiers to maintain an ever present photon population in the laser modes and to have an approximately constant carrier population. This enables faster response (switching times below 25 ps are reached in this work)than in conventional active optical flip-flop structures. The operation of the flip-flop is studied using a rate equation model accounting for the carrier densities and the complex electric fields in the different cavity modes of the laser amplifiers.     

Fast fault-tree evaluation for many sets of input data

It is pointed out that system unavailability and failure frequency can be found for many sets of components data via symbolic formulas with few multiplications. The derivation of such symbolic formulas is possible by binary-tree algorithms (specifically the Shannon expansion) which could run very fast on supercomputers allowing for binary-tree parallelism. The reduction factor of the number of multiplications needed in nested versus polynomial forms is roughly half the height of the decomposition tree, and the height of the tree is roughly the number of system components     

内存映射处理网络规划仿真大数据的研究

本文介绍了内存映射的基本原理与调用流程,通过内存映射文件技术解决了无线网络规划软件大数据量中间结果的文件读写效率问题,对传统文件技术与内存映射技术进行了性能对比,展示了软件通过中间结果文件生成的最终结果,使软件既能够满足大规模仿真的需求,同时保证了运行的高效性。     

The localization of spontaneous brain activity: an efficient way toanalyze large data sets

An efficient solution is presented of the problem to localize the electric generators of spontaneous magnetoencephalography (MEG) and electroencephalography (EEG) data for large data sets. When a data set contains more than 100,000 samples standard methods fail or become impractical. The method presented here is useful, for example, for the localization of (pathological) brain rhythms or the analysis of single-trial data.The problem is defined as finding the good fitting dipoles using the single-dipole model applied on each time sample. First, the data is bandpass filtered to select the rhythm of interest. Next, the empirical relationship between data power and probability of a dipole with a high goodness of fit (g.o.f.) is used to preselect data points. Then a global search algorithm is applied, based on precomputed lead fields on a fixed grid, to obtain a good initial guess for the nonlinear dipole search. Finally, the dipole search is applied on those samples that have a low initial guess error. In a group of five patients, it is found that 50% of the dipoles with a g.o.f. of at least 90% can be found by disregarding 90% of the data samples. Those dipoles can be found efficiently by disregarding all sample points with an initial guess relative residual error of 15% or lower. Finally, a simple empirical expression is found for the optimal mesh size of the global search grid. The method is completely automatic and makes it possible to study simple generators of large MEG and EEG data sets on a routine basis.     

Fast fixation of brain in situ by high intensity microwave irradiation: application to neurochemical studies.

The levels of acetylcholine and choline were measured in various brain regions of the rat after fixation by microwave irradiation of the head and after decapitation and subsequent freezing in liquid nitrogen. Levels of acetylcholine were increased by approximately 50% after microwave irradiation, while choline levels were reduced. These biochemical findings were correlated with virtually complex loss of acetylcholinesterase and NADH-diaphorase activity after 1 s exposure to microwave irradiation at a level of 5 kW.     

Fast image recovery using dynamic load balancing in parallelarchitectures, by means of incomplete projections

This paper formulates an incomplete projection algorithm that is applied to the image recovery problem. The algorithm allows an easy implementation of dynamic load balancing for parallel architectures. Furthermore, the local computation-communication load ratio can be adjusted, since each processor performs a finite number of iterations of any projection-type technique, and this number can be provided as a parameter of the algorithm. Numerical results compare favorably with those obtained by the extrapolated method of parallel subgradient projections.     

基于Rough集的信息融合目标识别方法

研究了Rough集理论在基于不同谱段光学信息融合的目标识别系统中的应用技术,在介绍了目标知识表示方法的基础上,提出了用C均值算法实现连续信息离散化的方法,并通过决策表属性的约简来生成决策表,以实现对目标的识别。针对可见光、中／长波红外等三种不同谱段下的三种不同目标图像进行了实验,实验结果表明,该方法具有对先验知识获取的易实现性和对目标识别的有效性。     

Fast algorithm for electromagnetic scattering by buried conductingplates of large size

This letter presents a fast algorithm for electromagnetic scattering by buried conducting plates of large size and arbitrary shape using the conjugate gradient (CG) method combined with the fast Fourier transform (FFT). Due to the use of FFT in handling the cyclic convolutions related to Toeplitz matrices, the Sommerfeld integrals' evaluation for the buried scattering problem, which is usually time consuming, has been reduced to a minimum. The memory required for this algorithm is of the order N-the number of unknowns-and the computational complexity is of order N_iterNlogN (N_iter is the iteration number N_iter≪N for large problems)     

An adaptive multirate algorithm for acquisition of fluorescence microscopy data sets.

We propose an algorithm for adaptive efficient acquisition of fluorescence microscopy data sets using a multirate (MR) approach. We simulate acquisition as part of a larger system for protein classification based on their subcellular location patterns and, thus, strive to maintain the achieved level of classification accuracy as much as possible. This problem is similar to image compression but unique due to additional restrictions, namely causality; we have access only to the information scanned up to that point. While we do want to acquire fewer samples with as low distortion as possible to achieve compression, our goal is to do so while affecting the overall classification accuracy as little as possible. We achieve this by using an adaptive MR scanning scheme which samples the regions of the image area that hold the most pertinent information. Our results show that we can achieve significant compression which we can then use to aquire faster or to increase space resolution of our data set, all while minimally affecting the classification accuracy of the entire system.     

Design of a large network for radiological image data.

Radiological imaging is a rapidly growing business. The field is quickly evolving from films to electronic or digital imaging. By the year 2015, the amount of radiological image data that will have been generated in the U.S. alone is projected to be between 100 and 300 000 PB. (1 PB equals 2(50) B or about 10(15) B.) As the volume of radiological data increases, the need to transmit the data over long distances also increases. For example, radiologists in Chicago, India, or Israel, working in the same medical practice, may read images taken in Chicago. Globally distributed research requires that images be transmitted around the world. Radiologists and researchers want to be able to download files containing hundreds of megabytes in seconds. This service requirement suggests that multiple copies of images should be retained in globally distributed databases to minimize access and transmission delays. Key design issues for such a database include the location of the data repositories relative to the generating and retrieval (reading) sites and the number and location of the copies of the files that are generated. In this paper, we approximate the time to retrieve images stored in city j by a radiologist in city k at time period t. Next, we formulate a model designed to minimize the average retrieval time weighted over all demands. We briefly outline a nested Lagrangian relaxation approach to the problem. Computational results are then summarized. The paper ends with conclusion and directions for future research.     

Radio source parameter estimation by maximum likelihood processing of variable baseline correlation interferometer data

The accurate joint determination of the direction and strength of a point noise source when the mutual coherence function of its radiated field is spatially sampled atMbaselines by a correlation interferometer is considered. The measurements are corrupted by the combined effects of a) the additive background and receiver noises at the interferometer antennas and b) the finite integration time of a practical correlator. The problem is approached from a statistical point of view (as contrasted with beam forming techniques). First the probability density function of the measurements is derived. The source's two parameters (direction and strength) are then jointly estimated using the maximum likelihood (ML) method. Investigation of the estimates' properties shows that they are virtually unbiased with variances that effectively attain the standard Cramer-Rao (C-R) lower bound when the number of measurements exceeds a "threshold" which is a decreasing function of the measurements' signal-to-noise ratio (SNR). The empirically observed fact that such a threshold is quite small, even at low SNR's, as well as the unbiasedness of the estimates, makes the performance of these (ML) estimates optimum for most practical applications.     

RBF network optimization of complex microwave systems represented by small FDTD modeling data sets

This paper outlines an original algorithm of neural optimization backed by three-dimensional full-wave finite-difference time-domain (FDTD) simulation and suitable for viable computer-aided design of complex microwave (MW) systems. The frequency response of an S-parameter is optimized with a decomposed radial basis function (RBF) network capable of dealing with various MW devices. The key feature of the optimization is the dynamic generation of as much FDTD data as the network needs to find a solution satisfying the constraints or the stopping criteria. Other functions contributing to the reduction of computational cost include a choice of an RBF type, radius optimization of the Gaussian RBF, optimization of the regularization parameter, etc. Performance of the algorithm is illustrated by its application to the systems, which can be adequately described only with the full-wave numerical analysis: a double waveguide window, a loaded MW oven, and a patch antenna with two long slits. In all these examples, the network demonstrates excellent generalizing capabilities with the use of relatively small data sets, and the optimized solutions are obtained within fairly reasonable time. The algorithm is shown to be advantageous over conventional gradient and nongradient local-optimization techniques because it is independent of the starting point and having the potential to find the "best" local optimum in the specified domain. Finally, parameters of FDTD simulations and the network operations influencing the computational cost of the optimization are thoroughly discussed.     

Identification of e.m. spectrum by known pole sets

A procedure for obtaining the e.m. poles of an object from its frequency-domain transfer function is applied to the scattered fields of three shiplike wire models. The possibility for identifying a particular ship model in the set of three from its pole set is examined.     

Exact reduced-complexity maximum likelihood reconstruction of multiple 3-D objects from unlabeled unoriented 2-D projections and electron microscopy of viruses.

In cryo-electron microscopy, the data is comprised of noisy 2-D projection images of the 3-D electron scattering intensity of the object where the orientation of the projections is unknown. Often, the images show randomly selected objects from a mixture of different types of objects. Objects of different type may be unrelated, e.g., different species of virus, or related, e.g., different conformations of the same species of virus. Due to the low SNR and the 2-D nature of the data, it is challenging to determine the type of the object shown in an individual image. A statistical model and maximum likelihood estimator that computes simultaneous 3-D reconstruction and labels using an expectation maximization algorithm exists but requires extensive computation due to the numerical evaluation of 3-D or 5-D integrations of a square matrix of dimension equal to the number of degrees of freedom in the 3-D reconstruction. By exploiting the geometry of rotations in 3-D, the estimation problem can be transformed so that the inner-most numerical integral has a scalar rather than a matrix integrand. This leads to a dramatic reduction in computation, especially as the number of degrees of freedom in the 3-D reconstruction increases. Numerical examples of the 3-D reconstructions are provided based on synthetic and experimental images where the objects are small spherical viruses.     

Identification of translational displacements between N-dimensional data sets using the high-order SVD and phase correlation.

This paper presents an extension of the phase correlation image alignment method to N-dimensional data sets. By the Fourier shift theorem, the motion model for translational shifts between N-dimensional images can be represented as a rank-one tensor. Through use of a high-order singular value decomposition, the phase correlation between two N-dimensional data sets can be decomposed to independently identify translational displacements along each dimension with subpixel resolution. Using three-dimensional MRI data sets, we demonstrate the effectiveness of this approach relative to other N-dimensional image registration methods.     

Quantitative images of large biological bodies in microwavetomography by using numerical and real data

A new inverse microwave imaging algorithm is presented which has the ability to obtain quantitative dielectric maps of large biological bodies. By using a priori information, obtained with a first order algorithm, the final image is obtained by solving the direct problem and an ill-conditioned system of equations into an iterative procedure. The algorithm has been successfully tested with real data from an experimental scanner