Judgments of path, not heading, guide locomotion

To steer a course through the world, people are almost entirely dependent on visual information, of which a key component is optic flow. In many models of locomotion, heading is described as the fundamental control variable; however, it has also been shown that fixating points along or near one's future path could be the basis of an efficient control solution. Here, the authors aim to establish how well observers can pinpoint instantaneous heading and path, by measuring their accuracy when looking at these features while traveling along straight and curved paths. The results showed that observers could identify both heading and path accurately (similar to 3 degrees) when traveling along straight paths, but on curved paths they were more accurate at identifying a point on their future path (similar to 5 degrees) than indicating their instantaneous heading (similar to 13 degrees). Furthermore, whereas participants could track changes in the tightness of their path, they were unable to accurately track the rate of change of heading. In light of these results, the authors suggest it is unlikely that heading is primarily used by the visual system to support active steering.

Verification and FPGA circuits of a block-2 fast path-based predictor

This paper formally derives a new path-based neural branch prediction algorithm (FPP) into blocks of size two for a lower hardware solution while maintaining similar input-output characteristic to the algorithm. The blocked solution, here referred to as B2P algorithm, is obtained using graph theory and retiming methods. Verification approaches were exercised to show that prediction performances obtained from the FPP and B2P algorithms differ within one mis-prediction per thousand instructions using a known framework for branch prediction evaluation. For a chosen FPGA device, circuits generated from the B2P algorithm showed average area savings of over 25% against circuits for the FPP algorithm with similar time performances thus making the proposed blocked predictor superior from a practical viewpoint.

FPGA organization for the fast path-based neural branch predictor

This paper develops cycle-level FPGA circuits of an organization for a fast path-based neural branch predictor Our results suggest that practical sizes of prediction tables are limited to around 32 KB to 64 KB in current FPGA technology due mainly to FPGA area of logic resources to maintain the tables. However the predictor scales well in terms of prediction speed. Table sizes alone should not be used as the only metric for hardware budget when comparing neural-based predictor to predictors of totally different organizations. This paper also gives early evidence to shift the attention on to the recovery from mis-prediction latency rather than on prediction latency as the most critical factor impacting accuracy of predictions for this class of branch predictors.

A relative path attenuation approximation algorithm for DVB-T systems

In the United Kingdom and in fact throughout Europe, the chosen standard for digital terrestrial television is the European Telecommunications Standards Institute (ETSI) ETN 300 744 also known as Digital Video Broadcasting - Terrestrial (DVB-T). The modulation method under this standard was chosen to be Orthogonal Frequency Division Multiplex (0FD4 because of the apparent inherent capability for withstanding the effects of multipath. Within the DVB-T standard, the addition of pilot tones was included that can be used for many applications such as channel impulse response estimation or local oscillator phase and frequency offset estimation. This paper demonstrates a technique for an estimation of the relative path attenuation of a single multipath signal that can be used as a simple firmware update for a commercial set-top box. This technique can be used to help eliminate the effects of multipath(1).

Full interference cancellation for two-path cooperative communications

This paper proposes a full interference cancellation (FIC) approach for two-path cooperative communications. Unlike the single relay schemes, the two-path cooperative scheme involves two relay nodes, so that the source can continuously transmit data to the two relays alternatively and the full bandwidth efficiency with respect to the direct transmission can be retained. The two-path relay scheme may however suffer from inter-relay interference which is caused by the simultaneous transmission of the source and one of the relays at any time. In this paper, first the inter-relay interference is expressed as a single recursive term in the received signal, and then the FIC approach is proposed to fully remove the inter-relay interference. The FIC has not only better performance but also less complexity than existing approaches. Numerical examples are also given to verify the proposed approach.

3D path planning with novel multiple 2D layered approach for complex human-robot interaction

Navigating cluttered indoor environments is a difficult problem in indoor service robotics. The Acroboter concept, a novel approach to indoor locomotion, represents unique opportunity to avoid obstacles in indoor environments by navigating the ceiling plane. This mode of locomotion requires the ability to accurately detect obstacles, and plan 3D trajectories through the environment. This paper presents the development of a resilient object tracking system, as well as a novel approach to generating 3D paths suitable for such robot configurations. Distributed human-machine interfacing allowing simulation previewing of actions is also considered in the developed system architecture.

Complexity of Monte Carlo algorithms for a class of integral equations

In this work we study the computational complexity of a class of grid Monte Carlo algorithms for integral equations. The idea of the algorithms consists in an approximation of the integral equation by a system of algebraic equations. Then the Markov chain iterative Monte Carlo is used to solve the system. The assumption here is that the corresponding Neumann series for the iterative matrix does not necessarily converge or converges slowly. We use a special technique to accelerate the convergence. An estimate of the computational complexity of Monte Carlo algorithm using the considered approach is obtained. The estimate of the complexity is compared with the corresponding quantity for the complexity of the grid-free Monte Carlo algorithm. The conditions under which the class of grid Monte Carlo algorithms is more efficient are given.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

An oblivious shortest-path routing algorithm for fully connected cubic networks

Fully connected cubic networks (FCCNs) are a class of newly proposed hierarchical interconnection networks for multicomputer systems, which enjoy the strengths of constant node degree and good expandability. The shortest path routing in FCCNs is an open problem. In this paper, we present an oblivious routing algorithm for n-level FCCN with N = 8(n) nodes, and prove that this algorithm creates a shortest path from the source to the destination. At the costs of both an O(N)-parallel-step off-line preprocessing phase and a list of size N stored at each node, the proposed algorithm is carried out at each related node in O(n) time. In some cases the proposed algorithm is superior to the one proposed by Chang and Wang in terms of the length of the routing path. This justifies the utility of our routing strategy. (C) 2006 Elsevier Inc. All rights reserved.

Full interference cancellation for two-path relay cooperative networks

This paper proposes the full interference cancellation (FIC) algorithm to cancel the inter-relay interference (IRI) in the two-path cooperative system. Arising from simultaneous data transmission from the source and relay nodes, IRI may significantly decrease the performance if it is not carefully handled. Compared to the existing partial interference cancellation (PIC) scheme, the FIC approach is more robust yet with less complexity. Numerical results are also given to verify the proposed scheme.

Multistep electrochemical reduction path of clusters [Os3(CO)10(α-diimine)]: comparison of electrochemical and photochemical Os-Os(α-diimine) bond cleavage

Electrochemical reduction of the triangular clusters [Os-3(CO)(10)(alpha-dimine)] (alpha-dimine = 2,2'-bipyridine (bpy), 2,2'-bipyrimidine (bpym)) and [Os-3(CO)(10)(mu-bpym) ReBr(CO)(3)] produces primarily the corresponding radical anions. Their stability is strongly determined by the pi acceptor ability of the reducible alpha-dimine ligand, which decreases in the order mu-bpym > bpym >> bpy. Along this series, increasing delocalisation of the odd electron density in the radical anion over the Os(alpha-dimine) chelate ring causes weakening of the axial (CO)(4)Os-Os(CO)(2)(alpha-dimine) bond and its facile cleavage for alpha-diimine = bpy. In contrast, the cluster radical anion is inherently stable for the bridging bpym ligand, the strongest pi-acceptor in the studied series. In the absence of the partial delocalisation of the unpaired electron over the Re( bpym) chelate bond, the Os-3-core of the radical anion remains intact only at low temperatures. Subsequent one-electron reduction of [Os-3(CO)(10)(bpym)](center dot-) at T = 223 K gives the open-triosmium core (= Os-3*) dianion, [Os-3*(CO)(10)(bpym)](2-). Its oxidation leads to the recovery of parent [Os-3(CO)(10)( bpym)]. At room temperature, [Os-3*( CO)(10)(bpym)](2-) is formed along a two-electron (ECE) reduction path. The chemical step (C) results in the formation of an open- core radical anion that is directly reducible at the cathodic potential of the parent cluster in the second electrochemical (E) step. In weakly coordinating tetrahydrofuran, [Os-3*(CO)(10)( bpym)](2-) rapidly attacks yet non- reduced parent cluster molecules, producing the relatively stable open- core dimer [Os-3*(CO)(10)(bpym)](2)(2-) featuring two open- triangle cluster moieties connected with an ( bpym) Os - Os( bpym) bond. In butyronitrile, [Os-3*( CO)(10)(bpym)](2-) is stabilised by the solvent and the dimer [Os-3*(CO)(10)(bpym)](2)(2-) is then mainly formed by reoxidation of the dianion on reverse potential scan. The more reactive cluster [Os-3(CO)(10)(bpy)] follows the same reduction path, as supported by spectroelectrochemical results and additional valuable evidence obtained from cyclic voltammetric scans. The ultimate process in the reduction mechanism is fragmentation of the cluster core triggered by the reduction of the dimer [Os-3*(CO)(10)(alpha- diimine)](2)(2-). The products formed are [Os-2(CO)(8)](2-) and {Os(CO)(2)(alpha- diimine)}(2). The latter dinuclear fragments constitute a linear polymeric chain [Os( CO)(2)(alpha-dimine)] n that is further reducible at the alpha-dimine ligands. For alpha-dimine = bpy, the charged polymer is capable of reducing carbon dioxide. The electrochemical opening of the triosmium core in the [Os-3( CO)(10)(alpha-dimine)] clusters exhibits several common features with their photochemistry. The same Os-alpha-dimine bond dissociates in both cases but the intimate mechanisms are different.

Solving complex optimal control problems at no cost with PSOPT

This paper introduces PSOPT, an open source optimal control solver written in C++. PSOPT uses pseudospectral and local discretizations, sparse nonlinear programming, automatic differentiation, and it incorporates automatic scaling and mesh refinement facilities. The software is able to solve complex optimal control problems including multiple phases, delayed differential equations, nonlinear path constraints, interior point constraints, integral constraints, and free initial and/or final times. The software does not require any non-free platform to run, not even the operating system, as it is able to run under Linux. Additionally, the software generates plots as well as LATEX code so that its results can easily be included in publications. An illustrative example is provided.

Condition number estimates for combined potential integral operators in acoustics and their boundary element discretisation

We consider the classical coupled, combined-field integral equation formulations for time-harmonic acoustic scattering by a sound soft bounded obstacle. In recent work, we have proved lower and upper bounds on the $L^2$ condition numbers for these formulations, and also on the norms of the classical acoustic single- and double-layer potential operators. These bounds to some extent make explicit the dependence of condition numbers on the wave number $k$, the geometry of the scatterer, and the coupling parameter. For example, with the usual choice of coupling parameter they show that, while the condition number grows like $k^{1/3}$ as $k\to\infty$, when the scatterer is a circle or sphere, it can grow as fast as $k^{7/5}$ for a class of `trapping' obstacles. In this paper we prove further bounds, sharpening and extending our previous results. In particular we show that there exist trapping obstacles for which the condition numbers grow as fast as $\exp(\gamma k)$, for some $\gamma>0$, as $k\to\infty$ through some sequence. This result depends on exponential localisation bounds on Laplace eigenfunctions in an ellipse that we prove in the appendix. We also clarify the correct choice of coupling parameter in 2D for low $k$. In the second part of the paper we focus on the boundary element discretisation of these operators. We discuss the extent to which the bounds on the continuous operators are also satisfied by their discrete counterparts and, via numerical experiments, we provide supporting evidence for some of the theoretical results, both quantitative and asymptotic, indicating further which of the upper and lower bounds may be sharper.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.