Options pricing is a critical problem and one of the fundamental building blocks in mathematical finance. Monte Carlo (MC) simulation is the most widely used solution for options pricing. In most cases options pricing must be performed in real time. Although today's multi-core CPUs can provide a high computing power, the options pricing on today's multi-core CPUs is far from responding in real time. In this paper, we use modern graphics processors (GPUs), which provide a much higher computing power than multi-core CPUs, to perform MC-based options pricing. The challenge is that GPUs only provide a small on-chip scratchpad while MC-based options pricing requires a large memory space and accesses the memory space irregularly. To make MC-based options pricing efficient on GPUs, we propose a recycling approach which compacts the data to shrink the memory space, and a crossing-path layout which reorganizes the data to make memory accesses GPU-friendly. We use real market data and benchmarks to evaluate our optimization approaches. The experimental result shows that our MC-based options pricing on the latest GPU is 43-fold faster than the latest multi-core CPU for single precision computation (with Intel C++ Compiler 11.1); compared with GCC 4.2.4, the speedup is as high as 145.

In the early days of the Internet layered design, the information between layers did not exchange in large amount frequently. With the rapid growth of the Internet, the emergence of many technologies such as service data partition, multi-connection and multi-path has made it possible to frequently exchange complex information between layers. With regard to these changes, this paper introduces ``network layered priority mapping (NLPM)" for future Internet development. The NLPM aims to maximize the satisfaction of the Internet users. The NLPM is designed to differentiate priority of the information on different layers and integrate the information using priority mapping. With NLPM, network services can be delivered more efficiently; network utilization such as the utilization of connection, path and channel can also be improved. Model analysis, NS simulation and prototype implementation have proved the efficiency of NLPM.

Centrality analysis has been shown to be a valuable method for the structural analysis of complex networks. It is used to identify key elements within networks and to rank network elements such that experiments can be tailored to interesting candidates. In this paper, we show that the optimization process of modularity density can be written in terms of the eigenspectrum of kernel matrix. Based on the eigenvectors belonging to the largest eigenvalue of kernel matrix, we present a new centrality measure that characterizes the contribution of each node to its assigned community in a network, called modularity density centrality. The measure is illustrated and compared with the standard centrality measures by using respectively an artificial example and a classic network data set. The statistical distribution of modularity density centrality is investigated by considering large computer generated graphs and two large networks from the real world. Experimental results show the significance of the proposed approach.

Precise concurrent zero-knowledge is a new notion introduced by Pandey et al. in Eurocrypt'08. This notion captures the idea that the view of any verifier in concurrent interaction can be reconstructed in almost the same time. Pandey et al. also constructed some precise concurrent zero-knowledge argument systems. In this paper we construct a precise bounded-concurrent zero-knowledge proof for NP, which has the precision p(n, y)=poly(n)+O(ny). Bounded-concurrency means that an a-priori bound on the number of concurrent sessions is specified before the protocol is constructed. Our result holds even if adversarial verifiers adopt the dynamic scheduling strategy. We make no setup assumption. The advantage of proof systems over argument systems is that the soundness property of proof systems can resist computationally-unbounded adversarial provers, while that of argument systems can only resist polynomial-time adversarial provers.

Unlike a Bézier curve, a spline curve is hard to be obtained through geometric corner cutting on control polygons because the degree elevation operator is difficult to be obtained and geometric convergence is hard to be achieved. In order to obtain geometric construction algorithm on C-B-splines, firstly we construct the degree elevation operator by using bi-order splines in this paper. Secondly we can obtain a control polygon sequence by degree elevation based on the degree elevation operator derived from a C-B-spline curve. Finally, we prove that this polygon sequence will converge to initial C-B-spline curve. This geometric construction algorithm possesses strong geometric intuition. It is also simple, stable and suitable for hardware to perform. This algorithm is important for CAD modeling systems, since many common engineering curves such as ellipse, helix, etc. can be represented explicitly by C-B-splines.

Using the limit point formula of the Loop subdivision scheme, we propose a very simple and efficient method for constructing interpolation surface of triangular meshes by Loop subdivision scheme. The excellent properties of the method are: (1) Locality: the perturbation of a given vertex only influences the surface shape near this vertex. (2) Efficiency: the locations of new points can be computed with explicit formulae. (3) Easiness in implementation: only the geometric rule of the first step should be modified. (4) Freedom: for each edge, there is one degree of freedom to adjust the shape of the interpolation surface. (5) Easiness in generalization: it is easy to generalize our method to other approximation subdivision schemes with explicit formulae to compute limit point.

Six kinds of emotions, namely joy, surprise, disgust, grief, anger and fear, are elicited from 300 ordinary college students by means of high-rated movie clips. The signals of galvanic skin response (GSR), heart rate (HR), blood volume pulse (BVP), electrocardiogram (ECG), respiration (Rsp.), facial electromyography (EMG) and two channels of electroencephalography (EEG) from the frontal lobe were recorded while the subjects were watching the affective eliciting materials. The samples of each kind of signals are analyzed by using random matrix theory (RMT). From the distribution of the eigenvalues and eigenvectors of the correlation matrices of BVP, facial EMG and two EEGs, we find that the statistical properties of these four kinds of signals coincide with the RMT predictions. However, the largest eigenvalue and the corresponding eigenvector component distribution of the correlation matrices of GSR, HR, ECG and Rsp. have deviated significantly from the RMT predictions. Our experiments also reveal that the correlations between two arbitrary samples of BVP, facial EMG or EEGs does not result from affective response but from random noises, whereas the amplitude variations of GSR, HR, ECG and Rsp. contain the correlated affective physiological response patterns. According to the data analysis results of RMT, 110 features are firstly extracted from the GSR and HR signals, and then a subset of the initial features is selected by using the Backward Selection algorithm. The affective data samples each of which is a vector of the features are classified by using a Fisher classifier, and furthermore, the user-independent emotion recognition systems with good prediction performance are constructed during the model selection process.

Skyline query processing has recently received a lot of attention in database community. Given a set of multi-dimensional objects, the skyline query finds the objects that are not dominated by others. To the best of our knowledge, the existing researches mainly focus on how to efficiently return the whole skyline set. However, as the cardinality and dimensionality of input dataset increase, the number of skylines grows exponentially, and hence this ``huge'' skyline set is completely useless to users. Motivated by the above fact, in this paper, we present a novel type of l-SkyDiv query, which only returns l skylines having maximum diversity, to improve the usefulness of skyline result. Also, we prove that the l-SkyDiv query belongs to the NP-Hard problem theoretically, and propose three efficient heuristic algorithms whose time complexities are polynomial to fast implement the proposed query. Furthermore, we present detailed theoretical analyses and extensive experiments, demonstrating that our algorithms are both efficient and effective.

A class of integral inequalities is transformed into homogeneous symmetric polynomial inequalities beyond Tarski model, where the number of elements of the polynomial, say n, is also a variable and the coefficients are functions of n. This is closely associated with some open problems formulated recently by Yang et al. Using Timofte's dimension-decreasing method for symmetric polynomial inequalities, combined with the inequality-proving package BOTTEMA and a program of implementing the method known as successive difference substitution, we provide a procedure for deciding the nonnegativity of the corresponding polynomial inequality such that the original integral inequality is mechanically decidable; otherwise, a counterexample will be given. The effectiveness of the algorithm is illustrated by some more examples.

In this paper, some properties of ordered information systems under homomorphism are investigated. The concept of a consistent function with respect to dominance relations is first introduced and its properties are investigated. Then, some main invariant properties of dominance relations under relation mappings are studied. It is proven that attribute reductions in the original ordered information system and its image system are equivalent under the condition of homomorphism. By means of the results, we can get the smaller image system that has the same reducts as a given massive ordered information system.

Space-time block codes based on complex orthogonal design have been widely investigated for their remarkable performance. In this paper, we propose a definition of more general complex orthogonal designs, which permits arbitrary complex factor with unit modulus in each entry. We prove that the maximal rate is still \frac{m+1}{2m} for n=2m or 2m-1 antennas and minimal delay is also lower-bounded by ({2m\atop m-1}). Thus, allowing complex factor with unit modulus in each entry will not improve the main performance criterion of space-time block codes.

In this paper, we analyze the frequency domain linear equalization (FDLE) of single carrier block transmission (SCBT) systems under fast fading channel. First, we propose a new approximating model in which the channel is assumed to be static in sub-blocks vary each other. Based on this model, we derive a new 2-orthogonal-sub-blocked frequency domain equalization method. Then, we derive the conditions of the channel under which the equalization method can be applied to the 2-orthogonal-sub-blocked systems. Simulation demonstrates that the proposed method can improve the anti-Doppler ability of SC-FDLE and at the same time keep its high efficiency and low complexity.

Multibaseline synthetic aperture radar (MB-SAR) can form a synthetic aperture in the height direction with multiple parallel observations, so it has the resolving capability in the height direction and can realize three-dimensional (3D) imaging for the target. The analytic model of MB-SAR based on spectrum estimation is analyzed in this paper. Based on the more general geometric model, we derive the signal model for MB-SAR 3D imaging. And then Yule-Walker algorithm is proposed to realize MB-SAR 3D imaging meanwhile the principle is analyzed and the steps of Yule-Walker algorithm are given. This algorithm can get the 3D image of the target with high resolution using fewer observations. Finally, the experimental results of MB-SAR 3D imaging using Yule-Walker algorithm are presented, which are generated with the simulated data and the data collected in anechoic chamber.

Transmit diversity multiple-input multiple-output (MIMO) radars decorrelate target echoes on distributed transmit array, and then through closely spaced receivers array estimate the angles of multiple targets using the received target echoes without separating transmitted signals. In this paper, the target echoes correlation is analyzed under Swerling I and II target model assumptions. The results show that: (1) Target echoes are uncorrelated under Swerling II model; (2) under Swerling I model, in order to decrease the correlation of target echoes by increasing the number of transmitters, it is required that the normalized covariance matrices of the signals before and after the transmitter number increases should satisfy a relation given in this study. Finally, the results are verified by computer simulations of the target echoes correlation and angles estimation performance.

The information of acceleration of a highly maneuverable target can be helpful to enhancing the performance of the tracker and facilitating the classification of targets. However, the current radars cannot provide information on the acceleration of the target in signal processing. Conventionally, acceleration is estimated by using Kalman filtering in several pulse echoes. There are limitations and shortcomings in this method because of its low precision. This paper proposes a Hough-ambiguity transformation (HAT) method for estimating the acceleration within one pulse. Simulations results validate the effectiveness of the proposed algorithm under several conditions with different pulse durations, signal to noise ratios (SNR), searching steps and searching radii respectively. Simulation results also show that the performance of the proposed method is superior to that of other methods.

The problem of auto-focusing imaging of 2D dielectric objects imbedded in a lossy earth is considered. Under Born approximation, the half-space spectrum Green's function is employed to formulate the half-space imaging algorithm from multi-frequency and multi-monostatic data. Hence the fast Fourier transform can be used to achieve real-time imaging in a very short computing time. Since the proposed algorithm has avoided the time-consuming regularization of a large-scale ill-posed matrix, the computing time can be greatly cut down. Inspired by the principle of time reversed imaging and the minimum entropy criterion, an auto-focusing imaging algorithm is presented to remove the image degradation caused by estimated error of the unknown dielectric parameters of the earth. Numerical results have shown that the proposed algorithm can provide good quality focused images for both low-contrast and high-contrast targets in a short computing time despite the inaccurate estimation of the earth electric parameters. The proposed algorithm can be extended to three-dimensional case naturally.

The accuracy of the satellite-measured reflectance is a key question for data processing and oceanographic applications. A hyperspectral satellite remote sensing reflectance evaluation model (HRSREM) was developed to evaluate the accuracy of the satellite measured reflectance. The model can compute the total reflectance at the top of the atmosphere (TOA) according to observation conditions of satellites, based on a radiative transfer model with the consideration of multiple scattering effects and atmospheric absorption effects. The performance of the HRSREM model was examined by Gordon's algorithms, showing that the relative errors of the Rayleigh scattering reflectance and the aerosol scattering reflectance are less than 2%. The model can also compute the sky reflectance which can be validated by in-situ measurements. The two sky reflectances match well with a spectral average error of 5.4%. The relative error of the total reflectance of the model, verified by sea-viewing wide field-of-view sensor (SeaWiFS) data, is about 3.5%. Therefore, the total reflectances at TOA, computed by the model, can be taken as reference values to evaluate the accuracy of satellite reflectances. The model was used to evaluate the accuracy of the hypersptral satellite (Hyperion) remote sensing data. The Hyperion reflectance matches the total reflectance of HRSREM very well at visible and near-infrared bands with an average error of 7.3%, while the status of calibration coefficients at shortwave infrared bands are not stable with a large spectral average error of 63.5%. The reflectance evaluation of a moderate resolution imaging spectrometer (CMODIS) data indicated that relative errors are large, especially at near-infrared bands with relative errors more than 100\%. The calibration coefficients of CMODIS, obtained from laboratory measurements, are not reliable. The CMODIS data should be recalibrated for oceanographic applications. The performance of the HRSREM model is effective in evaluating satellite data and its algorithms can be easily modified in order to evaluate the accuracy of other ocean color satellite sensors.

A high temperature superconducting (HTS) filter with a linear phase is designed for CDMA2000 communication systems. The principle and equivalent model of the filter have been presented. The theoretical result, coupling matrix, and the simulated result with Sonnet software have also been demonstrated. The desired filter with 12-pole and 2 cross couplings has a center frequency of 830 MHz. The measurement results show that the response of practical filters is in good agreement with that of simulated results and theoretical analysis, the group delay variation is less than ±10 ns over 60% of the filter bandwidth, and the skit slope of the filter is about 37 dB/MHz.

In commercial networks, autonomous user nodes operating on batteries are assumed to be selfish to consume their energy solely to maximize their own benefits, e.g., data throughputs. In this letter a two-user cooperative game is proposed to perform the power allocation for selfish cooperative communication networks. In the game, one selfish user node could trade its transmission power for the other ones cooperative relaying directly, and both user nodes are willing to achieve an optimal data-rate increase through cooperative relaying. To find the Nash bargaining solution (NBS) of the game, a low-complexity numerical particle swarm optimizer (PSO) algorithm is also developed. Simulation results indicate that the NBS of the game is efficient, in that both users could experience better performance than they work independently, and fair, in that the degree of cooperation of a user node only depends on how much contribution its partner can make to improve its own performance.

In this paper, a novel algorithm for color image enhancement is proposed. The proposed method, which is based on Retinex theory and total variational framework, improves the original variational method by using a TV penalty term to force spatial smoothness on the reflectance image. The split Bregman algorithm is employed to solve the proposed model. By practical experiments, it is verified that our method obtains better enhancement performance and much better calculation efficiency.