Optimization of Global Signal Networks for Island-Style FPGAs

We present a staggered buffer connection method that provides flexibility for buffer insertion while designing global signal networks using the tile-based FPGA design methodology. An exhaustive algorithm is used to analyze the trade-off between area and speed of the global signal networks for this staggered buffer insertion scheme, and the criterion for determining the design parameters is presented. The comparative analytic result shows that the methods in this paper are proven to be more efficient for FPGAs with a large array size.

Towards zero loss for tcp in wireless networks

IEEE Computer Society; IEEE Technical Committee on Simulation (TCSIM)

The critical lowest molecular weight for PEG to crystallize in cross-linked networks

Poly(ethylene glycol) (PEG) networks were synthesized by gamma-irradiation. The crystalline behavior of PEG was investigated by differential scanning calorimetry (DSC) and wide-angle X-ray diffraction (WAXD). It was shown that the crystallinity of PEG is dramatically lower in the cross-linked, networks than in pure PEG. When the molecular weight of PEG in the networks decreased to 1000, it could not crystallize at all. Moreover, we also found that the melting temperature of PEG is greatly affected by the presence of a cross-linked network.

Confined crystallization behavior of PEO in organic networks

Poly (ethylene oxide) (PEO) and poly (trimethopropane trimethacrylate) (PTMPTMA) interpenetrate networks have been synthesized. The confined crystallization behavior of PEO in the PTMTYTMA networks has been investigated by a differential scanning calorimeter and scanning electron microscope. The degree of PEO crystallinity in PEO/PTMPTMA interpenetrate networks reduces with the increase of PTMPTMA. PEO is in an amorphous state when the concentration of PEO is lower than 50% in the interpenetrate networks system. The melting points of crystalline PEO in the networks are lower than that of pure PEG, and the melting point of PEO in the networks is higher and increases with the increase of PEO in the interpenetrate networks. Wide-angle X-ray diffraction results show that the PEO crystallite size perpendicular to the (120) plane is not affected as much as PEO in silica networks. (C) 2001 Elsevier Science Ltd. All rights reserved.

Parallel Networks for Machine Vision

The amount of computation required to solve many early vision problems is prodigious, and so it has long been thought that systems that operate in a reasonable amount of time will only become feasible when parallel systems become available. Such systems now exist in digital form, but most are large and expensive. These machines constitute an invaluable test-bed for the development of new algorithms, but they can probably not be scaled down rapidly in both physical size and cost, despite continued advances in semiconductor technology and machine architecture. Simple analog networks can perform interesting computations, as has been known for a long time. We have reached the point where it is feasible to experiment with implementation of these ideas in VLSI form, particularly if we focus on networks composed of locally interconnected passive elements, linear amplifiers, and simple nonlinear components. While there have been excursions into the development of ideas in this area since the very beginnings of work on machine vision, much work remains to be done. Progress will depend on careful attention to matching of the capabilities of simple networks to the needs of early vision. Note that this is not at all intended to be anything like a review of the field, but merely a collection of some ideas that seem to be interesting.

Data analysis with artificial immune systems, cluster analysis and kohonen networks: some comparisons.

Neal M J Timmis J and Hunt J. Data analysis with artificial immune systems, cluster analysis and kohonen networks: some comparisons. In Proceedings of IEEE international conference of systems, man and cybernetics, pages 922-927, Tokyo, 1999. IEEE.

Qualitative Modelling of Linear Networks in Engineering Applications

Lee M.H., Qualitative Modelling of Linear Networks in Engineering Applications, in Proc. ECAI?2000, 14th European Conf. on Artificial Intelligence, Berlin, August 19th - 25th 2000, pp161-5.

Qualitative Modelling of Linear Networks in ECAD Applications

Lee M.H., Qualitative Modelling of Linear Networks in ECAD Applications, Proc. 13th Int. Workshop on Qualitative Reasoning, (QR'99), Loch Awe, Scotland, 1999, pp146-52.

Endocrine Inspired Modulation of Artificial Neural Networks for Mobile Robotics

Sauze, C and Neal, M. 'Endocrine Inspired Modulation of Artificial Neural Networks for Mobile Robotics', Dynamics of Learning Behavior and Neuromodulation Workshop, European Conference on Artifical Life 2007, Lisbon, Portugal, September 10th-14th 2007.

Causality enabled compositional modelling of Bayesian networks

J. Keppens and Q. Shen. Causality enabled compositional modelling of Bayesian networks. Proceedings of the 18th International Workshop on Qualitative Reasoning, pages 33-40, 2004.

Automated cross-modal mapping in robotic eye/hand systems using plastic radial basis function networks

Q. Meng and M. H Lee, Automated cross-modal mapping in robotic eye/hand systems using plastic radial basis function networks, Connection Science, 19(1), pp 25-52, 2007.