Ranging Accuracy in Dynamic Spectrum Access Networks

Theoretical analysis of time-of-arrival (TOA)-based high-precision ranging algorithm for the dynamic spectrum access networks (DSANs) is performed. The asymptotic frequency-domain Cramer-Rao bound (CRB) of the ranging algorithm that takes the frequency-dependent feature (FDF) and phase of multipath components (MPCs) into account is derived through Whittle formula. The effects of FDF-MPCs and related parameters such as absolute bandwidth and operating center frequency on the ranging accuracy are investigated. The results show that the impacts of the FDF-MPCs on the ranging accuracy can be significant and it is recommended utilizing as large absolute bandwidth as possible at low operating center frequencies to obtain high-precision distance information of the users in the DSANs     

Hierarchical Order Statistics Filtering for Fast Bi‐Dimensional Empirical Mode Decomposition

A hierarchical approach for fast bi‐dimensional empirical mode decomposition (B‐EMD) is proposed. The presented approach utilizes an efficient window size determination scheme that enables the multi‐level computation of the order statistics filter (OSF). Our detailed experiments show that the proposed OSF computation approach allows a significantly faster computation of an EMD without degrading the decomposition accuracy.     

Theoretical Limits for Time Delay Based Location Estimation in Cooperative Relay Networks

Node localization in wireless networks is crucial for supporting advanced location-based services and improving the performance of network algorithms such as routing schemes. In this paper, we study the fundamental limits for time delay based location estimation in cooperative relay networks. The theoretical limits are investigated by obtaining Cramer–Rao Lower Bound (CRLB) expressions for the unknown source location under different relaying strategies when the location of the destination is known and unknown. More specifically, the effects of amplify-and-forward and decode-and-forward relaying strategies on the location estimation accuracy are studied. Furthermore, the CRLB expressions are derived for the cases where the location of only source as well as both source and destination nodes are unknown considering the relays as reference nodes. In addition, the effects of the node topology on the location estimation accuracy of the source node are investigated. The results reveal that the relaying strategy at relay nodes, the number of relays, and the node topology can have significant impacts on the location accuracy of the source node. Additionally, knowing the location of the destination node is crucial for achieving accurate source localization in cooperative relay networks.     

Fundamental limits on time delay estimation in dispersed spectrum cognitive radio systems

In this paper, fundamental limits on time delay estimation are studied for cognitive radio systems, which facilitate opportunistic use of spectral resources. First, a generic Cramer-Rao lower bound (CRLB) expression is obtained in the case of unknown channel coefficients and carrier-frequency offsets (CFOs) for cognitive radio systems with dispersed spectrum utilization. Then, various modulation schemes are considered, and the effects of unknown channel coefficients and CFOs on the accuracy of time delay estimation are quantified. Finally, numerical studies are performed in order to verify the theoretical analysis.     

Microstructural characterization of corn starch‐based porous thermoplastic composites filled with multiwalled carbon nanotubes

Microstructural characterization of corn starch‐based porous thermoplastic (TPS) composites containing various contents (0.1, 0.5, and 1 wt %) of multiwalled carbon nanotubes (MWCNTs) was performed. Corn starch was plasticized with a proper combination of glycerol and stearic acid. TPS composites with MWCNT were prepared conducting melt extrusion followed by injection molding. TPS containing 1 wt % of MWCNTs exhibited higher tensile strength and elastic modulus values than neat TPS. Moreover, TPS electrical conductivity was determined to increase with increasing content of MWCNTs. X‐ray diffraction measurements revealed that incorporation of MWCNTs increased the degree of TPS crsystallinity to some extent. Scanning electron microscopy examination revealed that MWCNT altered TPS surface morphology and tensile failure modes, significantly. Transmission electron microscopy investigation showed that dispersion characteristics of MWCNTs within TPS were in the form of tiny clusters around micro pores of TPS, which is considered influential on electrical conductivity of the resulting composites. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

Effect of ZnO type and concentration on the mophology,thermal, and mechanical properties of poly(ether ester)/ZnO composites

Poly(ether ester) (PEE) copolymers were synthesized in a two‐stage process involving transesterification and polycondensation. The synthesized copolymer and the zinc oxide (ZnO) were used in composite preparation by melt compounding. The influence of ZnO type and concentration on the morphology, thermal and mechanical properties of the composites were studied. DSC and XRD analyses indicated that crystallinity of composites was slightly reduced with ZnO content. Homogeneous dispersion of fillers in the polymer matrix was observed through morphological analyses. While in general tensile strength and elongation at break values of the composites decreased with increasing ZnO content, elastic modulus values increased with the addition of ZnO. Moreover, ZnO particles were modified with poly(N‐vinyl pyrrolidone) and a slight improvement in mechanical properties was observed, respectively over the composites containing unmodified particles. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

Saliency detection based on hybrid artificial bee colony and firefly optimization

Pattern Analysis and Applications - Saliency detection is one of the challenging problems still tackled by image processing and computer vision research communities. Although not very numerous,...     

On the improvement of a scalable sparse direct solver for unsymmetrical linear equations

This paper focuses on the application level improvements in a sparse direct solver specifically used for large-scale unsymmetrical linear equations resulting from unstructured mesh discretization of coupled elliptic/hyperbolic PDEs. Existing sparse direct solvers are designed for distributed server systems taking advantage of both distributed memory and processing units. We conducted extensive numerical experiments with three state-of-the-art direct linear solvers that can work on distributed-memory parallel architectures; namely, MUMPS (MUMPS solver website, http://graal.ens-lyon.fr/MUMPS), WSMP (Technical Report TR RC-21886, IBM, Watson Research Center, Yorktown Heights, 2000), and SUPERLU_DIST (ACM Trans Math Softw 29(2):110–140, 2003). The performance of these solvers was analyzed in detail, using advanced analysis tools such as Tuning and Analysis Utilities (TAU) and Performance Application Programming Interface (PAPI). The performance is evaluated with respect to robustness, speed, scalability, and efficiency in CPU and memory usage. We have determined application level issues that we believe they can improve the performance of a distributed-shared memory hybrid variant of this solver, which is proposed as an alternative solver [SuperLU_MCDT (Many-Core Distributed)] in this paper. The new solver utilizing the MPI/OpenMP hybrid programming is specifically tuned to handle large unsymmetrical systems arising in reservoir simulations so that higher performance and better scalability can be achieved for a large distributed computing system with many nodes of multicore processors. Two main tasks are accomplished during this study: (i) comparisons of public domain solver algorithms; existing state-of-the-art direct sparse linear system solvers are investigated and their performance and weaknesses based on test cases are analyzed, (ii) improvement of direct sparse solver algorithm (SuperLU_MCDT) for many-core distributed systems is achieved. We provided results of numerical tests that were run on up to 16,384 cores, and used many sets of test matrices for reservoir simulations with unstructured meshes. The numerical results showed that SuperLU_MCDT can outperform SuperLU_DIST 3.3 in terms of both speed and robustness.     

Real-time implementation of order-statistics-based directional filters

Vector filters based on order-statistics have proved successful in removing impulsive noise from colour images while preserving edges and fine image details. Among these filters, the ones that involve the cosine distance function (directional filters) have particularly high computational requirements, which limits their use in time-critical applications. In this paper, we introduce two methods to speed up these filters. Experiments on a diverse set of colour images show that the proposed methods provide substantial computational gains without significant loss of accuracy.     

Parametric least squares approximation using gamma bases

We study the problem of linear approximation of a signal using the parametric gamma bases in L² space. These bases have a time scale parameter, which has the effect of modifying the relative angle between the signal and the projection space, thereby yielding an extra degree of freedom in the approximation. Gamma bases have a simple analog implementation that is a cascade of identical lowpass filters. We derive the normal equation for the optimum value of the time scale parameter and decouple it from that of the basis weights. Using statistical signal processing tools, we further develop a numerical method for estimating the optimum time scale