1,442 research outputs found
High Performance and Optimal Configuration of Accurate Heterogeneous Block-Based Approximate Adder
Approximate computing is an emerging paradigm to improve power and
performance efficiency for error-resilient application. Recent approximate
adders have significantly extended the design space of accuracy-power
configurable approximate adders, and find optimal designs by exploring the
design space. In this paper, a new energy-efficient heterogeneous block-based
approximate adder (HBBA) is proposed; which is a generic/configurable model
that can be transformed to a particular adder by defining some configurations.
An HBBA, in general, is composed of heterogeneous sub-adders, where each
sub-adder can have a different configuration. A set of configurations of all
the sub-adders in an HBBA defines its configuration. The block-based adders are
approximated through inexact logic configuration and truncated carry chains.
HBBA increases design space providing additional design points that fall on the
Pareto-front and offer better power-accuracy trade-off compared to other
configurations. Furthermore, to avoid Mont-Carlo simulations, we propose an
analytical modelling technique to evaluate the probability of error and
Probability Mass Function (PMF) of error value. Moreover, the estimation method
estimates delay, area and power of heterogeneous block-based approximate
adders. Thus, based on the analytical model and estimation method, the optimal
configuration under a given error constraint can be selected from the whole
design space of the proposed adder model by exhaustive search. The simulation
results show that our HBBA provides improved accuracy in terms of error metrics
compared to some state-of-the-art approximate adders. HBBA with 32 bits length
serves about 15% reduction in area and up to 17% reduction in energy compared
to state-of-the-art approximate adders.Comment: Submitted to the IEEE-TCAD journal, 16 pages, 16 figure
System data communication structures for active-control transport aircraft, volume 2
The application of communication structures to advanced transport aircraft are addressed. First, a set of avionic functional requirements is established, and a baseline set of avionics equipment is defined that will meet the requirements. Three alternative configurations for this equipment are then identified that represent the evolution toward more dispersed systems. Candidate communication structures are proposed for each system configuration, and these are compared using trade off analyses; these analyses emphasize reliability but also address complexity. Multiplex buses are recognized as the likely near term choice with mesh networks being desirable for advanced, highly dispersed systems
A unified view on weakly correlated recurrent networks
The diversity of neuron models used in contemporary theoretical neuroscience
to investigate specific properties of covariances raises the question how these
models relate to each other. In particular it is hard to distinguish between
generic properties and peculiarities due to the abstracted model. Here we
present a unified view on pairwise covariances in recurrent networks in the
irregular regime. We consider the binary neuron model, the leaky
integrate-and-fire model, and the Hawkes process. We show that linear
approximation maps each of these models to either of two classes of linear rate
models, including the Ornstein-Uhlenbeck process as a special case. The classes
differ in the location of additive noise in the rate dynamics, which is on the
output side for spiking models and on the input side for the binary model. Both
classes allow closed form solutions for the covariance. For output noise it
separates into an echo term and a term due to correlated input. The unified
framework enables us to transfer results between models. For example, we
generalize the binary model and the Hawkes process to the presence of
conduction delays and simplify derivations for established results. Our
approach is applicable to general network structures and suitable for
population averages. The derived averages are exact for fixed out-degree
network architectures and approximate for fixed in-degree. We demonstrate how
taking into account fluctuations in the linearization procedure increases the
accuracy of the effective theory and we explain the class dependent differences
between covariances in the time and the frequency domain. Finally we show that
the oscillatory instability emerging in networks of integrate-and-fire models
with delayed inhibitory feedback is a model-invariant feature: the same
structure of poles in the complex frequency plane determines the population
power spectra
Application of advanced on-board processing concepts to future satellite communications systems
An initial definition of on-board processing requirements for an advanced satellite communications system to service domestic markets in the 1990's is presented. An exemplar system architecture with both RF on-board switching and demodulation/remodulation baseband processing was used to identify important issues related to system implementation, cost, and technology development
Large Deviations Performance of Consensus+Innovations Distributed Detection with Non-Gaussian Observations
We establish the large deviations asymptotic performance (error exponent) of
consensus+innovations distributed detection over random networks with generic
(non-Gaussian) sensor observations. At each time instant, sensors 1) combine
theirs with the decision variables of their neighbors (consensus) and 2)
assimilate their new observations (innovations). This paper shows for general
non-Gaussian distributions that consensus+innovations distributed detection
exhibits a phase transition behavior with respect to the network degree of
connectivity. Above a threshold, distributed is as good as centralized, with
the same optimal asymptotic detection performance, but, below the threshold,
distributed detection is suboptimal with respect to centralized detection. We
determine this threshold and quantify the performance loss below threshold.
Finally, we show the dependence of the threshold and performance on the
distribution of the observations: distributed detectors over the same random
network, but with different observations' distributions, for example, Gaussian,
Laplace, or quantized, may have different asymptotic performance, even when the
corresponding centralized detectors have the same asymptotic performance.Comment: 30 pages, journal, submitted Nov 17, 2011; revised Apr 3, 201
Probabilistic Framework for the Positioning Of a Vehicle in a Combined Indoor-Outdoor Scenario
The development in technology has given
us all sophistications but equal amounts of
threats too. This has brought us an urge to
bring a complete security system that
monitors an object continuously. Consider
a situation where a cargo vehicle carrying
valuable material is moving in an area
using GPS (an outdoor sensor) we can
monitor it but the actual problem arises
when its movement involves both indoor
(with in the industry) and outdoor because
GPS has its limitations in indoor
environment. Hence it is essential to have
an additional sensor that would enable us a
continuous monitoring /tracking with out
cutoff of the signal. In this paper we bring
out a solution by combining Ultra wide
band (UWB) with GPS sensory information
which eliminates the limitations of
conventional tracking methods in mixed
scenario(indoor and outdoor) The same
method finds application in mobile robots,
monitoring a person on grounds of
security, etc
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