Implementation of Art1 and Art2 Artificial Neural Networks on Ring and Mesh Architectures

The Artificial Neural Networks (ANNs) are being used to solve a variety of problems in pattern recognition, robotic control, VLSI CAD and other areas. In most of these applications, a speedy response from the ANNs is imperative. However, ANNs comprise a large number of artificial neurons, and a massive interconnection network among them. Hence, implementation of these ANNs involves execution of computer-intensive operations. The usage of multiprocessor systems therefore becomes necessary. In this article, we have presented the implementation of ART1 and ART2 ANNs on ring and mesh architectures. The overall system design and implementation aspects are presented. The performance of the algorithm on ring, 2-dimensional mesh and n-dimensional mesh topologies is presented. The parallel algorithm presented for implementation of ART1 is not specific to any particular architecture. The parallel algorithm for ARTE is more suitable for a ring architecture.

Denoising neural data with state-space smoothing: Method and application

Neural data are inevitably contaminated by noise. When such noisy data are subjected to statistical analysis, misleading conclusions can be reached. Here we attempt to address this problem by applying a state-space smoothing method, based on the combined use of the Kalman filter theory and the Expectation–Maximization algorithm, to denoise two datasets of local field potentials recorded from monkeys performing a visuomotor task. For the first dataset, it was found that the analysis of the high gamma band (60–90 Hz) neural activity in the prefrontal cortex is highly susceptible to the effect of noise, and denoising leads to markedly improved results that were physiologically interpretable. For the second dataset, Granger causality between primary motor and primary somatosensory cortices was not consistent across two monkeys and the effect of noise was suspected. After denoising, the discrepancy between the two subjects was significantly reduced.

Mesh-free approximations via the error reproducing kernel method and applications to nonlinear systems developing shocks

Error estimates for the error reproducing kernel method (ERKM) are provided. The ERKM is a mesh-free functional approximation scheme [A. Shaw, D. Roy, A NURBS-based error reproducing kernel method with applications in solid mechanics, Computational Mechanics (2006), to appear (available online)], wherein a targeted function and its derivatives are first approximated via non-uniform rational B-splines (NURBS) basis function. Errors in the NURBS approximation are then reproduced via a family of non-NURBS basis functions, constructed using a polynomial reproduction condition, and added to the NURBS approximation of the function obtained in the first step. In addition to the derivation of error estimates, convergence studies are undertaken for a couple of test boundary value problems with known exact solutions. The ERKM is next applied to a one-dimensional Burgers equation where, time evolution leads to a breakdown of the continuous solution and the appearance of a shock. Many available mesh-free schemes appear to be unable to capture this shock without numerical instability. However, given that any desired order of continuity is achievable through NURBS approximations, the ERKM can even accurately approximate functions with discontinuous derivatives. Moreover, due to the variation diminishing property of NURBS, it has advantages in representing sharp changes in gradients. This paper is focused on demonstrating this ability of ERKM via some numerical examples. Comparisons of some of the results with those via the standard form of the reproducing kernel particle method (RKPM) demonstrate the relative numerical advantages and accuracy of the ERKM.

Multipath Dissemination in Regular Mesh Topologies

Mesh topologies are important for large-scale peer-to-peer systems that use low-power transceivers. The Quality of Service (QoS) in such systems is known to decrease as the scale increases. We present a scalable approach for dissemination that exploits all the shortest paths between a pair of nodes and improves the QoS. Despite th presence of multiple shortest paths in a system, we show that these paths cannot be exploited by spreading the messages over the paths in a simple round-robin manner; nodes along one of these paths will always handle more messages than the nodes along the other paths. We characterize the set of shortest paths between a pair of nodes in regular mesh topologies and derive rules, using this characterization, to effectively spread the messages over all the available paths. These rules ensure that all the nodes that are at the same distance from the source handle roughly the same number of messages. By modeling the multihop propagation in the mesh topology as a multistage queuing network, we present simulation results from a variety of scenarios that include link failures and propagation irregularities to reflect real-world characteristics. Our method achieves improved QoS in all these scenarios.

Finite volume TVD formulation of lattice Boltzmann simulation on unstructured mesh

A numerical scheme is presented for accurate simulation of fluid flow using the lattice Boltzmann equation (LBE) on unstructured mesh. A finite volume approach is adopted to discretize the LBE on a cell-centered, arbitrary shaped, triangular tessellation. The formulation includes a formal, second order discretization using a Total Variation Diminishing (TVD) scheme for the terms representing advection of the distribution function in physical space, due to microscopic particle motion. The advantage of the LBE approach is exploited by implementing the scheme in a new computer code to run on a parallel computing system. Performance of the new formulation is systematically investigated by simulating four benchmark flows of increasing complexity, namely (1) flow in a plane channel, (2) unsteady Couette flow, (3) flow caused by a moving lid over a 2D square cavity and (4) flow over a circular cylinder. For each of these flows, the present scheme is validated with the results from Navier-Stokes computations as well as lattice Boltzmann simulations on regular mesh. It is shown that the scheme is robust and accurate for the different test problems studied.

A new approach for fixed point smoothing in linear distributed parameter systems

In this paper, we solve the distributed parameter fixed point smoothing problem by formulating it as an extended linear filtering problem and show that these results coincide with those obtained in the literature using the forward innovations method.

Mesh Processing for Computerized Facial Anthropometry

Understanding of the shape and size of different features of the human body from scanned data is necessary for automated design and evaluation of product ergonomics. In this paper, a computational framework is presented for automatic detection and recognition of important facial feature regions, from scanned head and shoulder polyhedral models. A noise tolerant methodology is proposed using discrete curvature computations, band-pass filtering, and morphological operations for isolation of the primary feature regions of the face, namely, the eyes, nose, and mouth. Spatial disposition of the critical points of these isolated feature regions is analyzed for the recognition of these critical points as the standard landmarks associated with the primary facial features. A number of clinically identified landmarks lie on the facial midline. An efficient algorithm for detection and processing of the midline, using a point sampling technique, is also presented. The results obtained using data of more than 20 subjects are verified through visualization and physical measurements. A color based and triangle skewness based schemes for isolation of geometrically nonprominent features and ear region are also presented. [DOI: 10.1115/1.3330420]

Providing QoS to Real and Data Applications in WiMAX Mesh Networks

We consider the problem of centralized routing and scheduling for IEEE 802.16 mesh networks so as to provide Quality of Service (QoS) to individual real and interactive data applications. We first obtain an optimal and fair routing and scheduling policy for aggregate demands for different source- destination pairs. We then present scheduling algorithms which provide per flow QoS guarantees while utilizing the network resources efficiently. Our algorithms are also scalable: they do not require per flow processing and queueing and the computational requirements are modest. We have verified our algorithms via extensive simulations.

Reconfigurable Viterbi decoder on mesh connected multiprocessor architecture

In modern wireline and wireless communication systems, Viterbi decoder is one of the most compute intensive and essential elements. Each standard requires a different configuration of Viterbi decoder. Hence there is a need to design a flexible reconfigurable Viterbi decoder to support different configurations on a single platform. In this paper we present a reconfigurable Viterbi decoder which can be reconfigured for standards such as WCDMA, CDMA2000, IEEE 802.11, DAB, DVB, and GSM. Different parameters like code rate, constraint length, polynomials and truncation length can be configured to map any of the above mentioned standards. Our design provides higher throughput and scalable power consumption in various configuration of the reconfigurable Viterbi decoder. The power and throughput can also be optimized for different standards.

New a posteriori error estimator and adaptive mesh refinement strategy for 2-D crack problems

A posteriori error estimation and adaptive refinement technique for fracture analysis of 2-D/3-D crack problems is the state-of-the-art. The objective of the present paper is to propose a new a posteriori error estimator based on strain energy release rate (SERR) or stress intensity factor (SIF) at the crack tip region and to use this along with the stress based error estimator available in the literature for the region away from the crack tip. The proposed a posteriori error estimator is called the K-S error estimator. Further, an adaptive mesh refinement (h-) strategy which can be used with K-S error estimator has been proposed for fracture analysis of 2-D crack problems. The performance of the proposed a posteriori error estimator and the h-adaptive refinement strategy have been demonstrated by employing the 4-noded, 8-noded and 9-noded plane stress finite elements. The proposed error estimator together with the h-adaptive refinement strategy will facilitate automation of fracture analysis process to provide reliable solutions.

Analysis of the evanescent field coupling between a fiber and a planar waveguide using the explicit finite difference method with a nonuniform mesh (Journal Paper)

We investigate an optical waveguide system consisting of an unclad fiber core suspended at a constant distance parallel to the surface of a planar waveguide. The coupling and propagation of light in the combined system is studied using the three-dimensional explicit finite difference beam propagation method with a nonuniform mesh configuration. The power loss in the fiber and the field distribution in the waveguide are studied as a function of various parameters, such as index changes, index profile, and propagation distance, for the combined system.

Algorithms for Routing and Centralized Scheduling in IEEE 802.16 Mesh Networks

IEEE 802.16 standards for Wireless Metropolitan Area Networks (WMANs) include a mesh mode of operation for improving the coverage and throughput of the network. In this paper, we consider the problem of routing and centralized scheduling for such networks. We first fix the routing, which reduces the network to a tree. We then present a finite horizon dynamic programming framework. Using it we obtain various scheduling algorithms depending upon the cost function. Next we consider simpler suboptimal algorithms and compare their performances.

Past Queue Length Based Low-Overhead Link Scheduling in Multi-beam Wireless Mesh Networks

Wireless mesh networks with multi-beam capability at each node through the use of multi-antenna beamforming are becoming practical and attracting increased research attention. Increased capacity due to spatial reuse and increased transmission range are potential benefits in using multiple directional beams in each node. In this paper, we are interested in low-complexity scheduling algorithms in such multi-beam wireless networks. In particular, we present a scheduling algorithm based on queue length information of the past slots in multi-beam networks, and prove its stability. We present a distributed implementation of this proposed algorithm. Numerical results show that significant improvement in delay performance is achieved using the proposed multi-beam scheduling compared to omni-beam scheduling. In addition, the proposed algorithm is shown to achieve a significant reduction in the signaling overhead compared to a current slot queue length approach.

Weighted subspace methods and spatial smoothing: analysis and comparison

The effect of using a spatially smoothed forward-backward covariance matrix on the performance of weighted eigen-based state space methods/ESPRIT, and weighted MUSIC for direction-of-arrival (DOA) estimation is analyzed. Expressions for the mean-squared error in the estimates of the signal zeros and the DOA estimates, along with some general properties of the estimates and optimal weighting matrices, are derived. A key result is that optimally weighted MUSIC and weighted state-space methods/ESPRIT have identical asymptotic performance. Moreover, by properly choosing the number of subarrays, the performance of unweighted state space methods can be significantly improved. It is also shown that the mean-squared error in the DOA estimates is independent of the exact distribution of the source amplitudes. This results in a unified framework for dealing with DOA estimation using a uniformly spaced linear sensor array and the time series frequency estimation problems.