89,337 research outputs found
Six networks on a universal neuromorphic computing substrate
In this study, we present a highly configurable neuromorphic computing substrate and use it for emulating several types of neural networks. At the heart of this system lies a mixed-signal chip, with analog implementations of neurons and synapses and digital transmission of action potentials. Major advantages of this emulation device, which has been explicitly designed as a universal neural network emulator, are its inherent parallelism and high acceleration factor compared to conventional computers. Its configurability allows the realization of almost arbitrary network topologies and the use of widely varied neuronal and synaptic parameters. Fixed-pattern noise inherent to analog circuitry is reduced by calibration routines. An integrated development environment allows neuroscientists to operate the device without any prior knowledge of neuromorphic circuit design. As a showcase for the capabilities of the system, we describe the successful emulation of six different neural networks which cover a broad spectrum of both structure and functionality
QRAT+: Generalizing QRAT by a More Powerful QBF Redundancy Property
The QRAT (quantified resolution asymmetric tautology) proof system simulates
virtually all inference rules applied in state of the art quantified Boolean
formula (QBF) reasoning tools. It consists of rules to rewrite a QBF by adding
and deleting clauses and universal literals that have a certain redundancy
property. To check for this redundancy property in QRAT, propositional unit
propagation (UP) is applied to the quantifier free, i.e., propositional part of
the QBF. We generalize the redundancy property in the QRAT system by QBF
specific UP (QUP). QUP extends UP by the universal reduction operation to
eliminate universal literals from clauses. We apply QUP to an abstraction of
the QBF where certain universal quantifiers are converted into existential
ones. This way, we obtain a generalization of QRAT we call QRAT+. The
redundancy property in QRAT+ based on QUP is more powerful than the one in QRAT
based on UP. We report on proof theoretical improvements and experimental
results to illustrate the benefits of QRAT+ for QBF preprocessing.Comment: preprint of a paper to be published at IJCAR 2018, LNCS, Springer,
including appendi
A Universal Parallel Two-Pass MDL Context Tree Compression Algorithm
Computing problems that handle large amounts of data necessitate the use of
lossless data compression for efficient storage and transmission. We present a
novel lossless universal data compression algorithm that uses parallel
computational units to increase the throughput. The length- input sequence
is partitioned into blocks. Processing each block independently of the
other blocks can accelerate the computation by a factor of , but degrades
the compression quality. Instead, our approach is to first estimate the minimum
description length (MDL) context tree source underlying the entire input, and
then encode each of the blocks in parallel based on the MDL source. With
this two-pass approach, the compression loss incurred by using more parallel
units is insignificant. Our algorithm is work-efficient, i.e., its
computational complexity is . Its redundancy is approximately
bits above Rissanen's lower bound on universal compression
performance, with respect to any context tree source whose maximal depth is at
most . We improve the compression by using different quantizers for
states of the context tree based on the number of symbols corresponding to
those states. Numerical results from a prototype implementation suggest that
our algorithm offers a better trade-off between compression and throughput than
competing universal data compression algorithms.Comment: Accepted to Journal of Selected Topics in Signal Processing special
issue on Signal Processing for Big Data (expected publication date June
2015). 10 pages double column, 6 figures, and 2 tables. arXiv admin note:
substantial text overlap with arXiv:1405.6322. Version: Mar 2015: Corrected a
typ
Fluctuating hydrodynamics and turbulence in a rotating fluid: Universal properties
We analyze the statistical properties of three-dimensional () turbulence
in a rotating fluid. To this end we introduce a generating functional to study
the statistical properties of the velocity field . We obtain the master
equation from the Navier-Stokes equation in a rotating frame and thence a set
of exact hierarchical equations for the velocity structure functions for
arbitrary angular velocity . In particular we obtain the {\em
differential forms} for the analogs of the well-known von Karman-Howarth
relation for fluid turbulence. We examine their behavior in the limit of
large rotation. Our results clearly suggest dissimilar statistical behavior and
scaling along directions parallel and perpendicular to . The
hierarchical relations yield strong evidence that the nature of the flows for
large rotation is not identical to pure two-dimensional flows. To complement
these results, by using an effective model in the small- limit, within
a one-loop approximation, we show that the equal-time correlation of the
velocity components parallel to displays Kolmogorov scaling
, where as for all other components, the equal-time correlators scale
as in the inertial range where is a wavevector in . Our
results are generally testable in experiments and/or direct numerical
simulations of the Navier-Stokes equation in a rotating frame.Comment: 24 pages in preprint format; accepted for publication in Phys. Rev. E
(2011
Dynamic escape game
We introduce Dynamic Escape Game (DEC), a tool that provides emergency evacuation plans in situations where some of the escape paths may become unavailable at runtime. We formalize the setting as a reachability two-player turn-based game where the universal player has the power of inhibiting at runtime some moves to the existential player. Thus, the universal player can change the structure of the game arena along a play. DEC uses a graphical interface to depict the game and displays a winning play whenever it exists
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