We used a spiking neural network (SNN) to decode neural data recorded from a 96-electrode array in premotor/motor cortex while a rhesus monkey performed a point-to-point reaching arm movement task. We mapped a Kalman-filter neural prosthetic decode algorithm developed to predict the arm’s velocity on to the SNN using the Neural Engineering Framework and simulated it using Nengo, a freely available software package. A 20,000-neuron network matched the standard decoder’s prediction to within 0.03% (normalized by maximum arm velocity). A 1,600-neuron version of this network was within 0.27%, and run in real-time on a 3GHz PC. These results demonstrate that a SNN can implement a statistical signal processing algorithm widely used as the decoder in high-performance neural prostheses (Kalman filter), and achieve similar results with just a few thousand neurons. Hardware SNN implementations—neuromorphic chips—may offer power savings, essential for realizing fully-implantable cortically controlled prostheses.

Closed-form equations for second-order transfer functions of general arbitrarily coupled resistance-capacitance (RC) trees with multiple drivers are reported. The models allow precise delay and noise calculations for systems of coupled interconnects with guaranteed stability and represent the minimum complexity associated with this class of circuits. Their accuracy is extensively compared against other relevant models and is found to be better or comparable to more expensive models. All results are derived from a theoretical approach, and their physical basis is examined. The simplicity, accuracy, and generality of the models make them suitable for use in early signal integrity analyses of complex systems and incremental physical optimization. Index Terms-Crosstalk, delay and noise modeling in VLSI circuits, interconnect modeling, timing analysis, transfer function.

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References b Fig. 2 Radialion parterm offlrrsh mounred parch onfenno on rhermnlire slob (2t= I00 mnn) or/,=2.03 GHz U Kplane: ha-planeIn a second experiment, a microstrip patch antenna was attached directly to a thermalite block (440 x 215 x 100 mm) and the dipole-like radiation panems measured in an anechoic chamber. The results given in Figs. 20 and h show the effect of placing radar absorbent material (RAM) on the block ends to absorb the surface wave contribution. With no absorbent material the surface waves result in some secondary radiation at the block ends thus creating a ripple interference pattem. The surface wave excitation is clearly a polarisation-dependent propagation mechanism.Discussion and conc/usions: Surface wave propagation on walls has been theoretically and experimentally demonstrated for some typical building materials. The water content of the material has pronounced effect on the parameters. Field reinforcement near dry wall surfaces is likely to occur in practical WLAN scenarios, both around and within buildings. Ray-tracing and other field prediction techniques may require modification to account for the surface wave fields and the complex interactions taking place. Acknowledg,nents:Helpful discussions with R. Craven (DSTL) and P. Nobles (RMCS) are gratefully acknowledged.

Closed form equations for second order transfer functions of general arbitrarily-coupled RC trees with multiple drivers are reported.The models allow precise delay and noise calculations for systems of coupled interconnects with guaranteed stability, and represent the minimum complexity associated with this class of circuits. The simplicity, accuracy and generality of the models make them suitable for use in early delay and noise planning of global signals in complex systems.