9,096 research outputs found
Desynchronization: Synthesis of asynchronous circuits from synchronous specifications
Asynchronous implementation techniques, which measure logic delays at run time and activate registers accordingly, are inherently more robust than their synchronous counterparts, which estimate worst-case delays at design time, and constrain the clock cycle accordingly. De-synchronization is a new paradigm to automate the design of asynchronous circuits from synchronous specifications, thus permitting widespread adoption of asynchronicity, without requiring special design skills or tools. In this paper, we first of all study different protocols for de-synchronization and formally prove their correctness, using techniques originally developed for distributed deployment of synchronous language specifications. We also provide a taxonomy of existing protocols for asynchronous latch controllers, covering in particular the four-phase handshake protocols devised in the literature for micro-pipelines. We then propose a new controller which exhibits provably maximal concurrency, and analyze the performance of desynchronized circuits with respect to the original synchronous optimized implementation. We finally prove the feasibility and effectiveness of our approach, by showing its application to a set of real designs, including a complete implementation of the DLX microprocessor architectur
Asynchronous Nano-Electronics: Preliminary Investigation
This paper is a preliminary investigation in implementing
asynchronous QDI logic in molecular nano-electronics,
taking into account the restricted geometry, the lack of control
on transistor strengths, the high timing variations. We
show that the main building blocks of QDI logic can be successfully
implemented; we illustrate the approach with the
layout of an adder stage. The proposed techniques to improve
the reliability of QDI apply to nano-CMOS as well
Event-based Vision: A Survey
Event cameras are bio-inspired sensors that differ from conventional frame
cameras: Instead of capturing images at a fixed rate, they asynchronously
measure per-pixel brightness changes, and output a stream of events that encode
the time, location and sign of the brightness changes. Event cameras offer
attractive properties compared to traditional cameras: high temporal resolution
(in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low
power consumption, and high pixel bandwidth (on the order of kHz) resulting in
reduced motion blur. Hence, event cameras have a large potential for robotics
and computer vision in challenging scenarios for traditional cameras, such as
low-latency, high speed, and high dynamic range. However, novel methods are
required to process the unconventional output of these sensors in order to
unlock their potential. This paper provides a comprehensive overview of the
emerging field of event-based vision, with a focus on the applications and the
algorithms developed to unlock the outstanding properties of event cameras. We
present event cameras from their working principle, the actual sensors that are
available and the tasks that they have been used for, from low-level vision
(feature detection and tracking, optic flow, etc.) to high-level vision
(reconstruction, segmentation, recognition). We also discuss the techniques
developed to process events, including learning-based techniques, as well as
specialized processors for these novel sensors, such as spiking neural
networks. Additionally, we highlight the challenges that remain to be tackled
and the opportunities that lie ahead in the search for a more efficient,
bio-inspired way for machines to perceive and interact with the world
Index to NASA Tech Briefs, 1975
This index contains abstracts and four indexes--subject, personal author, originating Center, and Tech Brief number--for 1975 Tech Briefs
Performance of direct-oversampling correlator-type receivers in chaos-based DS-CDMA systems over frequency non-selective fading channels
In this paper, we present a study on the performance of direct-oversampling correlator-type receivers in chaos-based direct-sequence code division multiple access systems over frequency non-selective fading channels. At the input, the received signal is sampled at a sampling rate higher than the chip rate. This oversampling step is used to precisely determine the delayed-signal components from multipath fading channels, which can be combined together by a correlator for the sake of increasing the SNR at its output. The main advantage of using direct-oversampling correlator-type receivers is not only their low energy consumption due to their simple structure, but also their ability to exploit the non-selective fading characteristic of multipath channels to improve the overall system performance in scenarios with limited data speeds and low energy requirements, such as low-rate wireless personal area networks. Mathematical models in discrete-time domain for the conventional transmitting side with multiple access operation, the generalized non-selective Rayleigh fading channel, and the proposed receiver are provided and described. A rough theoretical bit-error-rate (BER) expression is first derived by means of Gaussian approximation. We then define the main component in the expression and build its probability mass function through numerical computation. The final BER estimation is carried out by integrating the rough expression over possible discrete values of the PFM. In order to validate our findings, PC simulation is performed and simulated performance is compared with the corresponding estimated one. Obtained results show that the system performance get better with the increment of the number of paths in the channel.Peer ReviewedPostprint (author's final draft
Dead Time Compensation for High-Flux Ranging
Dead time effects have been considered a major limitation for fast data
acquisition in various time-correlated single photon counting applications,
since a commonly adopted approach for dead time mitigation is to operate in the
low-flux regime where dead time effects can be ignored. Through the application
of lidar ranging, this work explores the empirical distribution of detection
times in the presence of dead time and demonstrates that an accurate
statistical model can result in reduced ranging error with shorter data
acquisition time when operating in the high-flux regime. Specifically, we show
that the empirical distribution of detection times converges to the stationary
distribution of a Markov chain. Depth estimation can then be performed by
passing the empirical distribution through a filter matched to the stationary
distribution. Moreover, based on the Markov chain model, we formulate the
recovery of arrival distribution from detection distribution as a nonlinear
inverse problem and solve it via provably convergent mathematical optimization.
By comparing per-detection Fisher information for depth estimation from high-
and low-flux detection time distributions, we provide an analytical basis for
possible improvement of ranging performance resulting from the presence of dead
time. Finally, we demonstrate the effectiveness of our formulation and
algorithm via simulations of lidar ranging.Comment: Revision with added estimation results, references, and figures, and
modified appendice
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