310 resultados para Growing neural gas


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With the emergence of voltage scaling as one of the most powerful power reduction techniques, it has been important to support voltage scalable statistical static timing analysis (SSTA) in deep submicrometer process nodes. In this paper, we propose a single delay model of logic gate using neural network which comprehensively captures process, voltage, and temperature variation along with input slew and output load. The number of simulation programs with integrated circuit emphasis (SPICE) required to create this model over a large voltage and temperature range is found to be modest and 4x less than that required for a conventional table-based approach with comparable accuracy. We show how the model can be used to derive sensitivities required for linear SSTA for an arbitrary voltage and temperature. Our experimentation on ISCAS 85 benchmarks across a voltage range of 0.9-1.1V shows that the average error in mean delay is less than 1.08% and average error in standard deviation is less than 2.85%. The errors in predicting the 99% and 1% probability point are 1.31% and 1%, respectively, with respect to SPICE. The two potential applications of voltage-aware SSTA have been presented, i.e., one for improving the accuracy of timing analysis by considering instance-specific voltage drops in power grids and the other for determining optimum supply voltage for target yield for dynamic voltage scaling applications.

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Corrosion of SAE 310 stainless steel in H2-H2O-H2S gas mixtures was studied at a constant temperature of 1150 K. Reactive gas mixtures were chosen to yield a constant oxygen potential of approximately 6 × 10-13 Nm-2 and sulfur potentials ranging from 0.19 × 10-2 Nm-2 to 33 × 10-2 Nm-2. The kinetics of corrosion were determined using a thermobalance, and the scales were analyzed using metallography, scanning electron microscopy, and energy dispersive X-ray analysis. Two corrosion regimes, which were dependent on sulfur potential, were identified. At high sulfur potentials (P S 2 ± 2.7 × 10-2 Nm-2) the corrosion rates were high, the kinetics obeyed a linear rate equation, and the scales consisted mainly of sulfide phases similar to those observed from pure sulfidation. At low sulfur potentials (P S 2 ± 0.19 × 10-2 Nm-2) the corrosion rates were low, the kinetics obeyed a parabolic rate equation, and scales consisted mainly of oxide phases. Thermochemical diagrams for the Fe-Cr-S-O, Fe-Ni-S-O, Cr-Ni-S-O, and Si-Cr-S-O systems were constructed, and the experimental results are discussed in relation to these diagrams. Based on this comparison, reasonable corrosion mechanisms were developed. At high sulfur potentials, oxide and sulfide phases initially nucleate as separate islands. Overgrowth of the oxide by the sulfide occurs and an exchange reaction governs the corrosion process. Preoxidation at low oxygen potentials and 1150 K is beneficial in suppressing sulfidation at high sulfur potentials.

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EMF measurements were made with an electrochemical cell of the type ~t/&(s)/&+-beta alumina/Ag~S(s)S. 2(g). S(s or 1)/R at temperatures between 95 and 241°C. Sflver $- alumina was prepared with the ion exchange technique. The patial pressure of diatomic gas obtained from cell voltages agreed with the literature data.

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Dense (Ba1―xLax)2In2O5+x (BLIO) electrolytes with different compositions (x = 0.4, 0.5, 0.6) were fabricated using powders obtained by the Pechini method. The formation of BLIO powders was investigated by using X-ray diffraction and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy. The calcination temperature and time were optimized. The sintered (Ba1―xLax)2In2O5+x electrolytes showed a relative density greater than ∼97%, and the major phase of three electrolyte compositions was indexed as a cubic perovskite. The electrical conductivity of BLIO ceramics at elevated temperatures in air was measured by ac-impedance spectroscopy. The activation energies for conduction in BLIO were 102 kJ mol―1 between 473 and 666 K and 118 kJ mol―1 between 769 and 873 K, which are comparable to that for 8 mol % yttria-stabilized cubic zirconia. Mixed-potential gas sensors utilizing BLIO-based electrolytes exhibited good sensitivity to different CO concentrations from ∼100 to ∼500 ppm and excellent selectivity to methane at around 873 K.

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We generalize the Nozieres-Schmitt-Rink method to study the repulsive Fermi gas in the absence of molecule formation, i.e., in the so-called ``upper branch.'' We find that the system remains stable except close to resonance at sufficiently low temperatures. With increasing scattering length, the energy density of the system attains a maximum at a positive scattering length before resonance. This is shown to arise from Pauli blocking which causes the bound states of fermion pairs of different momenta to disappear at different scattering lengths. At the point of maximum energy, the compressibility of the system is substantially reduced, leading to a sizable uniform density core in a trapped gas. The change in spin susceptibility with increasing scattering length is moderate and does not indicate any magnetic instability. These features should also manifest in Fermi gases with unequal masses and/or spin populations.

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Chronic recording of neural signals is indispensable in designing efficient brain–machine interfaces and to elucidate human neurophysiology. The advent of multichannel micro-electrode arrays has driven the need for electronics to record neural signals from many neurons. The dynamic range of the system can vary over time due to change in electrode–neuron distance and background noise. We propose a neural amplifier in UMC 130 nm, 1P8M complementary metal–oxide–semiconductor (CMOS) technology. It can be biased adaptively from 200 nA to 2 $mu{rm A}$, modulating input referred noise from 9.92 $mu{rm V}$ to 3.9 $mu{rm V}$. We also describe a low noise design technique which minimizes the noise contribution of the load circuitry. Optimum sizing of the input transistors minimizes the accentuation of the input referred noise of the amplifier and obviates the need of large input capacitance. The amplifier achieves a noise efficiency factor of 2.58. The amplifier can pass signal from 5 Hz to 7 kHz and the bandwidth of the amplifier can be tuned for rejecting low field potentials (LFP) and power line interference. The amplifier achieves a mid-band voltage gain of 37 dB. In vitro experiments are performed to validate the applicability of the neural low noise amplifier in neural recording systems.

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The storage capacity of an activated carbon bed is studied using a 2D transport model with constant inlet flow conditions. The predicted filling times and variation in bed pressure and temperature are in good agreement with experimental observations obtained using a 1.82 L prototype ANG storage cylinder. Storage efficiencies based on the maximum achievable V/V (volume of gas/volume of container) and filling times are used to quantify the performance of the charging process. For the high permeability beds used in the experiments, storage efficiencies are controlled by the rate of heat removal. Filling times, defined as the time at which the bed pressure reaches 3.5 MPa, range from 120 to 3.4 min for inlet flow rates of 1.0 L min(-1) and 30.0 L min(-1), respectively. The corresponding storage efficiencies, eta(s), vary from 90% to 76%, respectively. Simulations with L/D ratios ranging from 0.35 to 7.8 indicate that the storage efficiencies can be improved with an increase in the LID ratios and/or with water cooled convection. Thus for an inlet flow rate of 30.0 L min(-1), an eta(s) value of 90% can be obtained with water cooling for an L/D ratio of 7.8 and a filling time of a few minutes. In the absence of water cooling the eta(s) value reduces to 83% at the same L/D ratio. Our study suggests that with an appropriate choice of cylinder dimensions, solutions based on convective cooling during adsorptive storage are possible with some compromise in the storage capacity.