Reconfigurable Digital Logic Gate Based on Neuromorphic Approach
01 Jan 2019-pp 506-507
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30 Jun 1995
TL;DR: The Hierarchy of Limits of Power J.D. Stratakos, et al., and Low Power Programmable Computation coauthored with M.B. Srivastava, provide a review of the main approaches to Voltage Scaling Approaches.
Abstract: 1. Introduction. 2. Hierarchy of Limits of Power J.D. Meindl. 3. Sources of Power Consumption. 4. Voltage Scaling Approaches. 5. DC Power Supply Design in Portable Systems coauthored with A.J. Stratakos, et al. 6. Adiabatic Switching L. Svensson. 7. Minimizing Switched Capacitance. 8. Computer Aided Design Tools. 9. A Portable Multimedia Terminal. 10. Low Power Programmable Computation coauthored with M.B. Srivastava. 11. Conclusions. Subject Index.
1,017 citations
"Reconfigurable Digital Logic Gate B..." refers background in this paper
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TL;DR: This paper shows that complementary CMOS is the logic style of choice for the implementation of arbitrary combinational circuits if low voltage, low power, and small power-delay products are of concern.
Abstract: Recently reported logic style comparisons based on full-adder circuits claimed complementary pass-transistor logic (CPL) to be much more power-efficient than complementary CMOS. However, new comparisons performed on more efficient CMOS circuit realizations and a wider range of different logic cells, as well as the use of realistic circuit arrangements demonstrate CMOS to be superior to CPL in most cases with respect to speed, area, power dissipation, and power-delay products. An implemented 32-b adder using complementary CMOS has a power-delay product of less than half that of the CPL version. Robustness with respect to voltage scaling and transistor sizing, as well as generality and ease-of-use, are additional advantages of CMOS logic gates, especially when cell-based design and logic synthesis are targeted. This paper shows that complementary CMOS is the logic style of choice for the implementation of arbitrary combinational circuits if low voltage, low power, and small power-delay products are of concern.
844 citations
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TL;DR: Gate diffusion input (GDI) - a new technique of low-power digital combinatorial circuit design - is described, showing advantages and drawbacks of GDI compared to other methods.
Abstract: Gate diffusion input (GDI) - a new technique of low-power digital combinatorial circuit design - is described. This technique allows reducing power consumption, propagation delay, and area of digital circuits while maintaining low complexity of logic design. Performance comparison with traditional CMOS and various pass-transistor logic design techniques is presented. The different methods are compared with respect to the layout area, number of devices, delay, and power dissipation. Issues like technology compatibility, top-down design, and precomputing synthesis are discussed, showing advantages and drawbacks of GDI compared to other methods. Several logic circuits have been implemented in various design styles. Their properties are discussed, simulation results are reported, and measurements of a test chip are presented.
275 citations
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TL;DR: A low-power analog circuit for implementing a model of a leaky integrate and fire neuron that includes elements for implementing spike frequency adaptation, for setting an arbitrary refractory period and for modulating the neuron's threshold voltage is presented.
Abstract: We present a low-power analog circuit for implementing a model of a leaky integrate and fire neuron. Next to being optimized for low-power consumption, the proposed circuit includes elements for implementing spike frequency adaptation, for setting an arbitrary refractory period and for modulating the neuron's threshold voltage. We present experimental data from a prototype chip, implemented using a standard 1.5 /spl mu/m CMOS process.
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TL;DR: An implementation of the Izhikevich neuron model which uses two first-order log-domain low-pass filters and two translinear multipliers to emulate different spiking behaviours observed in biological neurons is presented.
Abstract: We present an implementation of the Izhikevich neuron model which uses two first-order log-domain low-pass filters and two translinear multipliers. The neuron consists of a leaky-integrate-and-fire core, a slow adaptive state variable and quadratic positive feedback. Simulation results show that this neuron can emulate different spiking behaviours observed in biological neurons.
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